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This study aims to assess the uncertain effect that the three major film cooling parameters exert on the global and fixed-cord-averaged film cooling effectiveness under low, medium, and high blowing ratios "}}]}, "properties": [], "parentId": "230", "childIds": [], "backendDOMNodeId": 691}, {"nodeId": "568", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "230", "childIds": ["1722"], "backendDOMNodeId": 692, "browsergym_id": "0bc71c75-1431-4d33"}, {"nodeId": "569", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ". The three input parameters include coolant hole diameter ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ". The three input parameters include coolant hole diameter "}}]}, "properties": [], "parentId": "230", "childIds": [], "backendDOMNodeId": 694}, {"nodeId": "570", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "230", "childIds": ["1723"], "backendDOMNodeId": 695, "browsergym_id": "4bbb4d9c-8d45-4701"}, {"nodeId": "571", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ", coolant tube inclination angle ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", coolant tube inclination angle "}}]}, "properties": [], "parentId": "230", "childIds": [], "backendDOMNodeId": 697}, {"nodeId": "572", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "230", "childIds": ["1724"], "backendDOMNodeId": 698, "browsergym_id": "e43574e4-a763-47bf"}, {"nodeId": "573", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ", and density ratio ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", and density ratio "}}]}, "properties": [], "parentId": "230", "childIds": [], "backendDOMNodeId": 700}, {"nodeId": "574", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "230", "childIds": ["1725"], "backendDOMNodeId": 701, "browsergym_id": "25b88b1a-bb20-42b1"}, {"nodeId": "575", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ". The training dataset is obtained by Computational Fluid Dynamics (CFD). Moreover, a seven-layer artificial neural network (ANN) algorithm is applied to explore the complex non-linear mapping between the input flat film cooling parameters and the output fixed-cord-averaged film cooling effectiveness on the external turbine blade surface. The sensitivity experiment conducted using Monte Carlo (MC) simulation shows that the ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ". The training dataset is obtained by Computational Fluid Dynamics (CFD). Moreover, a seven-layer artificial neural network (ANN) algorithm is applied to explore the complex non-linear mapping between the input flat film cooling parameters and the output fixed-cord-averaged film cooling effectiveness on the external turbine blade surface. The sensitivity experiment conducted using Monte Carlo (MC) simulation shows that the "}}]}, "properties": [], "parentId": "230", "childIds": [], "backendDOMNodeId": 703}, {"nodeId": "576", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "230", "childIds": ["1726"], "backendDOMNodeId": 704, "browsergym_id": "5c6fafb0-524a-4a49"}, {"nodeId": "577", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " and ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " and "}}]}, "properties": [], "parentId": "230", "childIds": [], "backendDOMNodeId": 706}, {"nodeId": "578", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "230", "childIds": ["1727"], "backendDOMNodeId": 707, "browsergym_id": "b650a20f-e390-4c15"}, {"nodeId": "579", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " are the two most sensitive parameters in the low-blowing-ratio cases. The ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " are the two most sensitive parameters in the low-blowing-ratio cases. The "}}]}, "properties": [], "parentId": "230", "childIds": [], "backendDOMNodeId": 709}, {"nodeId": "580", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "230", "childIds": ["1728"], "backendDOMNodeId": 710, "browsergym_id": "5f86a185-8609-4a1f"}, {"nodeId": "581", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " comes to be the only leading factor of sensitivity in larger blowing ratio cases. As the blowing ratio rises, the uncertainty of the three parameters ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " comes to be the only leading factor of sensitivity in larger blowing ratio cases. As the blowing ratio rises, the uncertainty of the three parameters "}}]}, "properties": [], "parentId": "230", "childIds": [], "backendDOMNodeId": 712}, {"nodeId": "582", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "230", "childIds": ["1729"], "backendDOMNodeId": 713, "browsergym_id": "267344cf-e901-495d"}, {"nodeId": "583", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " and ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " and "}}]}, "properties": [], "parentId": "230", "childIds": [], "backendDOMNodeId": 715}, {"nodeId": "584", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "230", "childIds": ["1730"], "backendDOMNodeId": 716, "browsergym_id": "a1d4e818-d47b-4b5a"}, {"nodeId": "585", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " all decrease. The combined effect of the three parameters is also dissected and shows that it has a more significant influence on the general cooling effectiveness than any single effect. The ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " all decrease. The combined effect of the three parameters is also dissected and shows that it has a more significant influence on the general cooling effectiveness than any single effect. The "}}]}, "properties": [], "parentId": "230", "childIds": [], "backendDOMNodeId": 718}, {"nodeId": "586", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "230", "childIds": ["1731"], "backendDOMNodeId": 719, "browsergym_id": "6cef3097-3b25-4597"}, {"nodeId": "587", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " has the widest variation of uncertainty interval at three blowing ratios, while the ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " has the widest variation of uncertainty interval at three blowing ratios, while the "}}]}, "properties": [], "parentId": "230", "childIds": [], "backendDOMNodeId": 721}, {"nodeId": "588", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "230", "childIds": ["1732"], "backendDOMNodeId": 722, "browsergym_id": "97a4e1c9-dad2-4c9e"}, {"nodeId": "589", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " has the largest uncertain influence on the general cooling effectiveness. With the aforementioned results, the cooling effectiveness of the gas turbine can be furthermore enhanced.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " has the largest uncertain influence on the general cooling effectiveness. With the aforementioned results, the cooling effectiveness of the gas turbine can be furthermore enhanced."}}]}, "properties": [], "parentId": "230", "childIds": [], "backendDOMNodeId": 724}, {"nodeId": "590", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "Introduction", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "Introduction"}}]}, "properties": [], "parentId": "233", "childIds": [], "backendDOMNodeId": 729}, {"nodeId": "591", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "In gas turbine applications, since the intake gas temperature positively correlates with the power output, the temperature of the intake gas is expected to be as high as possible in pursuit of a better power output of a gas turbine. However, such temperature typically exceeds the melting temperature of turbine blades, which would cause the blade to melt and even lead to potential dangers in a gas turbine (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "In gas turbine applications, since the intake gas temperature positively correlates with the power output, the temperature of the intake gas is expected to be as high as possible in pursuit of a better power output of a gas turbine. However, such temperature typically exceeds the melting temperature of turbine blades, which would cause the blade to melt and even lead to potential dangers in a gas turbine ("}}]}, "properties": [], "parentId": "234", "childIds": [], "backendDOMNodeId": 731}, {"nodeId": "592", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "1", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "1"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "234", "childIds": ["1733"], "backendDOMNodeId": 732, "browsergym_id": "b4671883-eeda-47fb"}, {"nodeId": "593", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "). Therefore, it is crucial to develop effective cooling methods to prevent potential overheating problems and avoid operating in overheated environments. Among a diverse selection of cooling methods, film cooling is the preferred and widely accepted choice in practical applications. A jet of coolant is extracted from the compressor and sprayed out from the coolant hole drilled on the flat blade in a designed geometric orientation. This jet of cooling air soon conflates the mainstream and then quickly covers the top surface of the blade, serving as an interlayer between the superheated mainstream air and the blades to prevent the blades from making direct contact with the hot mainstream. This process helps to prolong the service life of the blade.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "). Therefore, it is crucial to develop effective cooling methods to prevent potential overheating problems and avoid operating in overheated environments. Among a diverse selection of cooling methods, film cooling is the preferred and widely accepted choice in practical applications. A jet of coolant is extracted from the compressor and sprayed out from the coolant hole drilled on the flat blade in a designed geometric orientation. This jet of cooling air soon conflates the mainstream and then quickly covers the top surface of the blade, serving as an interlayer between the superheated mainstream air and the blades to prevent the blades from making direct contact with the hot mainstream. This process helps to prolong the service life of the blade."}}]}, "properties": [], "parentId": "234", "childIds": [], "backendDOMNodeId": 734}, {"nodeId": "594", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "Nonetheless, the process of predicting the cooling effects from a given flat plate hole parameter set is complicated by the complexity and unpredictability of the vortex structure and gas mixing motion. Previous studies have shown that two categories of input parameters matter to the resulting film cooling efficiency. They include the property of the coolant jet and the coolant injection method. The thermal property of the coolant includes coolant temperature (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "Nonetheless, the process of predicting the cooling effects from a given flat plate hole parameter set is complicated by the complexity and unpredictability of the vortex structure and gas mixing motion. Previous studies have shown that two categories of input parameters matter to the resulting film cooling efficiency. They include the property of the coolant jet and the coolant injection method. The thermal property of the coolant includes coolant temperature ("}}]}, "properties": [], "parentId": "235", "childIds": [], "backendDOMNodeId": 736}, {"nodeId": "595", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "2", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "2"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "235", "childIds": ["1734"], "backendDOMNodeId": 737, "browsergym_id": "ab2cd077-62eb-4825"}, {"nodeId": "596", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ") or coolant-to-mainstream temperature ratio (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ") or coolant-to-mainstream temperature ratio ("}}]}, "properties": [], "parentId": "235", "childIds": [], "backendDOMNodeId": 739}, {"nodeId": "597", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "3", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "3"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "235", "childIds": ["1735"], "backendDOMNodeId": 740, "browsergym_id": "0279fe34-214b-4e83"}, {"nodeId": "598", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "). Garg et al. (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "). Garg et al. ("}}]}, "properties": [], "parentId": "235", "childIds": [], "backendDOMNodeId": 742}, {"nodeId": "599", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "2", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "2"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "235", "childIds": ["1736"], "backendDOMNodeId": 743, "browsergym_id": "cb3c13a1-82e9-48b4"}, {"nodeId": "600", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ") delved into the impact of coolant temperature exerted on adiabatic effectiveness of the gas turbine blades by applying Navier-Stokes codes. Han et al. (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ") delved into the impact of coolant temperature exerted on adiabatic effectiveness of the gas turbine blades by applying Navier-Stokes codes. Han et al. ("}}]}, "properties": [], "parentId": "235", "childIds": [], "backendDOMNodeId": 745}, {"nodeId": "601", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "3", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "3"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "235", "childIds": ["1737"], "backendDOMNodeId": 746, "browsergym_id": "ad9679b6-8385-4205"}, {"nodeId": "602", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ") concluded that the mainstream-to-coolant jet temperature ratio impacts the film cooling effectiveness greatly, and better cooling performance is achieved at higher temperature. The dynamic coolant properties of coolant contain coolant density ratio (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ") concluded that the mainstream-to-coolant jet temperature ratio impacts the film cooling effectiveness greatly, and better cooling performance is achieved at higher temperature. The dynamic coolant properties of coolant contain coolant density ratio ("}}]}, "properties": [], "parentId": "235", "childIds": [], "backendDOMNodeId": 748}, {"nodeId": "603", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "4", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "4"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "235", "childIds": ["1738"], "backendDOMNodeId": 749, "browsergym_id": "80c43c4a-ebbb-4574"}, {"nodeId": "604", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ") and blowing ratio (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ") and blowing ratio ("}}]}, "properties": [], "parentId": "235", "childIds": [], "backendDOMNodeId": 751}, {"nodeId": "605", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "5", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "5"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "235", "childIds": ["1739"], "backendDOMNodeId": 752, "browsergym_id": "6e21e67c-ad88-412a"}, {"nodeId": "606", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "). Sinha (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "). Sinha ("}}]}, "properties": [], "parentId": "235", "childIds": [], "backendDOMNodeId": 754}, {"nodeId": "607", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "6", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "6"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "235", "childIds": ["1740"], "backendDOMNodeId": 755, "browsergym_id": "d3627526-3d8d-464b"}, {"nodeId": "608", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ") found that increasing the density ratio would create a negative lifting effect that promotes the spreading of the coolant jet heavily, and thus, impaired the film cooling effectiveness significantly. Cao et al. (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ") found that increasing the density ratio would create a negative lifting effect that promotes the spreading of the coolant jet heavily, and thus, impaired the film cooling effectiveness significantly. Cao et al. ("}}]}, "properties": [], "parentId": "235", "childIds": [], "backendDOMNodeId": 757}, {"nodeId": "609", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "7", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "7"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "235", "childIds": ["1741"], "backendDOMNodeId": 758, "browsergym_id": "f82332bc-adca-415f"}, {"nodeId": "610", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ") outlined that with the continuous increasing of blowing ratio, the film cooling effect first rises and then falls. The coolant injection method contains the cooling hole shape (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ") outlined that with the continuous increasing of blowing ratio, the film cooling effect first rises and then falls. The coolant injection method contains the cooling hole shape ("}}]}, "properties": [], "parentId": "235", "childIds": [], "backendDOMNodeId": 760}, {"nodeId": "611", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "8", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "8"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "235", "childIds": ["1742"], "backendDOMNodeId": 761, "browsergym_id": "dfda32fb-f0d1-4a9b"}, {"nodeId": "612", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "), compound angle (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "), compound angle ("}}]}, "properties": [], "parentId": "235", "childIds": [], "backendDOMNodeId": 763}, {"nodeId": "613", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "9", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "9"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "235", "childIds": ["1743"], "backendDOMNodeId": 764, "browsergym_id": "b95aaa95-6172-4ec0"}, {"nodeId": "614", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "), inclination angle (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "), inclination angle ("}}]}, "properties": [], "parentId": "235", "childIds": [], "backendDOMNodeId": 766}, {"nodeId": "615", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "10", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "10"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "235", "childIds": ["1744"], "backendDOMNodeId": 767, "browsergym_id": "1230ff58-0b8b-4161"}, {"nodeId": "616", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "), and exit lateral diffusion angles (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "), and exit lateral diffusion angles ("}}]}, "properties": [], "parentId": "235", "childIds": [], "backendDOMNodeId": 769}, {"nodeId": "617", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "11", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "11"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "235", "childIds": ["1745"], "backendDOMNodeId": 770, "browsergym_id": "2910f9a0-43e7-4bb5"}, {"nodeId": "618", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "). Gritsch et al. (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "). Gritsch et al. ("}}]}, "properties": [], "parentId": "235", "childIds": [], "backendDOMNodeId": 772}, {"nodeId": "619", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "8", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "8"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "235", "childIds": ["1746"], "backendDOMNodeId": 773, "browsergym_id": "43408746-4c93-4e54"}, {"nodeId": "620", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ") concluded that hole shapes significantly impact the film cooling effectiveness. Most studies have shown that coolant hole diameter, coolant tube inclination angle, density ratio", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ") concluded that hole shapes significantly impact the film cooling effectiveness. Most studies have shown that coolant hole diameter, coolant tube inclination angle, density ratio"}}]}, "properties": [], "parentId": "235", "childIds": [], "backendDOMNodeId": 775}, {"nodeId": "621", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "235", "childIds": ["1747"], "backendDOMNodeId": 776, "browsergym_id": "b6e28789-86e0-40cc"}, {"nodeId": "622", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " and blowing ratio play a good role in film cooling effectiveness. Thus, a performance analysis on these elements is warranted.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " and blowing ratio play a good role in film cooling effectiveness. Thus, a performance analysis on these elements is warranted."}}]}, "properties": [], "parentId": "235", "childIds": [], "backendDOMNodeId": 778}, {"nodeId": "623", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "Uncertainty analysis is of great importance in gas turbines (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "Uncertainty analysis is of great importance in gas turbines ("}}]}, "properties": [], "parentId": "236", "childIds": [], "backendDOMNodeId": 780}, {"nodeId": "624", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "12", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "12"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "236", "childIds": ["1748"], "backendDOMNodeId": 781, "browsergym_id": "b9f0366e-9e60-4c3b"}, {"nodeId": "625", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "). Different parameters influence the behavior of the gas turbine differently. Even slight variations of some specific parameters could bring considerable differences in the performance of the gas turbine. However, most previous uncertainty quantification studies are conducted based on conventional and inefficient Polynomial Chaos Expansion (PCE) models. Akbar et al. (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "). Different parameters influence the behavior of the gas turbine differently. Even slight variations of some specific parameters could bring considerable differences in the performance of the gas turbine. However, most previous uncertainty quantification studies are conducted based on conventional and inefficient Polynomial Chaos Expansion (PCE) models. Akbar et al. ("}}]}, "properties": [], "parentId": "236", "childIds": [], "backendDOMNodeId": 783}, {"nodeId": "626", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "13", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "13"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "236", "childIds": ["1749"], "backendDOMNodeId": 784, "browsergym_id": "436dba35-8adc-4382"}, {"nodeId": "627", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ") surveyed seven uncertainty parameters in total and performed the uncertainty quantification analysis by the PCE method for film cooling. Shi et al. (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ") surveyed seven uncertainty parameters in total and performed the uncertainty quantification analysis by the PCE method for film cooling. Shi et al. ("}}]}, "properties": [], "parentId": "236", "childIds": [], "backendDOMNodeId": 786}, {"nodeId": "628", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "14", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "14"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "236", "childIds": ["1750"], "backendDOMNodeId": 787, "browsergym_id": "9480888e-d30b-4c81"}, {"nodeId": "629", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ") used a PCE method to evaluate the uncertain effect of the conical angles etc. on discharge coefficient and adiabatic cooling effectiveness. Mathiodakis et al. (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ") used a PCE method to evaluate the uncertain effect of the conical angles etc. on discharge coefficient and adiabatic cooling effectiveness. Mathiodakis et al. ("}}]}, "properties": [], "parentId": "236", "childIds": [], "backendDOMNodeId": 789}, {"nodeId": "630", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "15", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "15"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "236", "childIds": ["1751"], "backendDOMNodeId": 790, "browsergym_id": "17005199-363d-4c74"}, {"nodeId": "631", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ")implemented research on the effect of ambient humidity on gas turbine performance and found that under high working temperatures, the impact that humidity has on the gas turbine is much more severe compared with low working temperatures. Huang et al. (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ")implemented research on the effect of ambient humidity on gas turbine performance and found that under high working temperatures, the impact that humidity has on the gas turbine is much more severe compared with low working temperatures. Huang et al. ("}}]}, "properties": [], "parentId": "236", "childIds": [], "backendDOMNodeId": 792}, {"nodeId": "632", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "16", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "16"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "236", "childIds": ["1752"], "backendDOMNodeId": 793, "browsergym_id": "4bda47c5-19ec-4f99"}, {"nodeId": "633", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ") also applied uncertainty quantification in their study of the heat transfer performance on rotor blade squealer tips.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ") also applied uncertainty quantification in their study of the heat transfer performance on rotor blade squealer tips."}}]}, "properties": [], "parentId": "236", "childIds": [], "backendDOMNodeId": 795}, {"nodeId": "634", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "However, the computation time and computation load increase exponentially in cases of higher dimensions, and the traditional PCE methods are commonly used to solve the \u201csingle output\u201d problem, i.e., it is more widely used to obtain the overall cooling temperature of the research region only, instead of the fix-cord-averaged temperature analysis. Even though theoretically, the PCE methods can also be utilized to produce laterally averaged results, the computational cost is relatively higher. Many beneficial attempts are conducted to solve the difficulties in high-dimensional cases, such as the surrogate-based optimization method and artificial neural network et al., to conclude the complex non-linear correlation between the input coolant parameter configurations and the resulting cooling effectiveness using semi-empirical correlations. Mellor et al. (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "However, the computation time and computation load increase exponentially in cases of higher dimensions, and the traditional PCE methods are commonly used to solve the \u201csingle output\u201d problem, i.e., it is more widely used to obtain the overall cooling temperature of the research region only, instead of the fix-cord-averaged temperature analysis. Even though theoretically, the PCE methods can also be utilized to produce laterally averaged results, the computational cost is relatively higher. Many beneficial attempts are conducted to solve the difficulties in high-dimensional cases, such as the surrogate-based optimization method and artificial neural network et al., to conclude the complex non-linear correlation between the input coolant parameter configurations and the resulting cooling effectiveness using semi-empirical correlations. Mellor et al. ("}}]}, "properties": [], "parentId": "237", "childIds": [], "backendDOMNodeId": 797}, {"nodeId": "635", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "17", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "17"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "237", "childIds": ["1753"], "backendDOMNodeId": 798, "browsergym_id": "dda43fd0-6056-4bc3"}, {"nodeId": "636", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ") accomplished that by finding and validating a semi-empirical correlation. However, the computation is still very complicated.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ") accomplished that by finding and validating a semi-empirical correlation. However, the computation is still very complicated."}}]}, "properties": [], "parentId": "237", "childIds": [], "backendDOMNodeId": 800}, {"nodeId": "637", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "In recent years, deep learning has emerged and is making a favorable contribution in pushing the process of various application fields forward (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "In recent years, deep learning has emerged and is making a favorable contribution in pushing the process of various application fields forward ("}}]}, "properties": [], "parentId": "238", "childIds": [], "backendDOMNodeId": 802}, {"nodeId": "638", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "18", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "18"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "238", "childIds": ["1754"], "backendDOMNodeId": 803, "browsergym_id": "e2b50c63-d446-4466"}, {"nodeId": "639", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "). In fluid mechanics, a surrogate model based on deep learning is a beneficial tool for setting up the complicated non-linear, and obscure relation between two data sets. Ma et al. (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "). In fluid mechanics, a surrogate model based on deep learning is a beneficial tool for setting up the complicated non-linear, and obscure relation between two data sets. Ma et al. ("}}]}, "properties": [], "parentId": "238", "childIds": [], "backendDOMNodeId": 805}, {"nodeId": "640", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "19", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "19"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "238", "childIds": ["1755"], "backendDOMNodeId": 806, "browsergym_id": "eb5ea382-303c-43bb"}, {"nodeId": "641", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ") investigated the behavior of the combustion chamber in a rocket. They utilized a convolutional neural network to forecast relations between coolant jet film and mainstream hot jet. Dolati et al. (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ") investigated the behavior of the combustion chamber in a rocket. They utilized a convolutional neural network to forecast relations between coolant jet film and mainstream hot jet. Dolati et al. ("}}]}, "properties": [], "parentId": "238", "childIds": [], "backendDOMNodeId": 808}, {"nodeId": "642", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "20", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "20"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "238", "childIds": ["1756"], "backendDOMNodeId": 809, "browsergym_id": "6f5dba0c-5714-4d05"}, {"nodeId": "643", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ") studied the film cooling effectiveness by building a GMDH-type neural network to model the plasma actuator effects over a flat plate. Yang et al. (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ") studied the film cooling effectiveness by building a GMDH-type neural network to model the plasma actuator effects over a flat plate. Yang et al. ("}}]}, "properties": [], "parentId": "238", "childIds": [], "backendDOMNodeId": 811}, {"nodeId": "644", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "21", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "21"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "238", "childIds": ["1757"], "backendDOMNodeId": 812, "browsergym_id": "b3a270c6-128d-44e1"}, {"nodeId": "645", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ") employed convolution modeling to predict the plugging problems and cooling efficiency of transpiration film cooling in the study. Wang et al. (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ") employed convolution modeling to predict the plugging problems and cooling efficiency of transpiration film cooling in the study. Wang et al. ("}}]}, "properties": [], "parentId": "238", "childIds": [], "backendDOMNodeId": 814}, {"nodeId": "646", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "22", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "22"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "238", "childIds": ["1758"], "backendDOMNodeId": 815, "browsergym_id": "cb561c90-e960-418b"}, {"nodeId": "647", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ") utilized a GRU neural network model to research a variety of cooling parameters in one dimension to forecast the trench film cooling effectiveness. It is deduced that it is accessible to use deep learning methods in film cooling research. Furthermore, Wang et al. also applied a supervised ANN on a SVG cooling configuration to explore the non-linear mapping between parameters and performance and conclude that when the blowing ratio is low, the radius of SVG dominates the cooling effectiveness (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ") utilized a GRU neural network model to research a variety of cooling parameters in one dimension to forecast the trench film cooling effectiveness. It is deduced that it is accessible to use deep learning methods in film cooling research. 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The application of the ANN model greatly enhanced the reliability of the correlation between parameters and the performance of the flat film cooling. The four cooling parameters include coolant hole diameter ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "This paper constructed and validated a deep-learning-based ANN model to obtain the dataset to identify a non-linear mapping to link the four cooling parameters to cooling effectiveness. The application of the ANN model greatly enhanced the reliability of the correlation between parameters and the performance of the flat film cooling. 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", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", and then we conducted uncertain effects of these film-cooling parameters at different blowing ratios. 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Due to the deviation of the cross-section area, this paper guarantees that the velocity of the jet inflow right at the coolant exit would accelerate to ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ". 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The problem is solved by applying steady-state solvers, which function by performing several iterations until the result converges. The standard to determine convergence is by comparing the continuity residual with 10", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "). The problem is solved by applying steady-state solvers, which function by performing several iterations until the result converges. 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If using a machine with 56 CPU to obtain the 225 datasets, it takes approximately 675 (225 ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "). If using a machine with 56 CPU to obtain the 225 datasets, it takes approximately 675 (225 "}}]}, "properties": [], "parentId": "254", "childIds": [], "backendDOMNodeId": 1059}, {"nodeId": "770", "ignored": false, "role": {"type": "role", "value": "generic"}, "chromeRole": {"type": "internalRole", "value": 88}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "254", "childIds": ["1838", "1839"], "backendDOMNodeId": 1060, "browsergym_id": "0c242014-708d-4fc1"}, {"nodeId": "771", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " hours. The mainstream and coolant inlet are assumed as velocity boundary conditions, and the mainstream outlet pressure is set to be 1\u00a0atm. Adiabatic and no-slip wall boundaries are applied for the mainstream and coolant chamber walls. Both flows are treated as superheated ideal gas, which follows the ideal gas law and is incompressible for low speed. The buoyancy effect is not assumed following Wang et al. (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " hours. The mainstream and coolant inlet are assumed as velocity boundary conditions, and the mainstream outlet pressure is set to be 1\u00a0atm. Adiabatic and no-slip wall boundaries are applied for the mainstream and coolant chamber walls. Both flows are treated as superheated ideal gas, which follows the ideal gas law and is incompressible for low speed. The buoyancy effect is not assumed following Wang et al. 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In ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " is truncated because the constant mainstream temperature is assumed. In "}}]}, "properties": [], "parentId": "269", "childIds": [], "backendDOMNodeId": 2877}, {"nodeId": "933", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 2A", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 2A"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "269", "childIds": ["1940"], "backendDOMNodeId": 2878, "browsergym_id": "6e9b3a7e-751d-4c7f"}, {"nodeId": "934", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ", the central-line film cooling effectiveness of the outer surface of the blade is computed ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", the central-line film cooling effectiveness of the outer surface of the blade is computed "}}]}, "properties": [], "parentId": "269", "childIds": [], "backendDOMNodeId": 2880}, {"nodeId": "935", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "269", "childIds": ["1941"], "backendDOMNodeId": 2881, "browsergym_id": "14135e10-5090-43d5"}, {"nodeId": "936", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " four numerical methods and two sets of experimental data. ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " four numerical methods and two sets of experimental data. 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The results indicate that the MAEs for the SA and Realizable k-\u03b5 models are larger than the SST k-\u03c9 and RNG k-\u03b5 models. Furthermore, the trend of the RNG k-\u03b5 model results matched better with the data obtained from the experiments. The MAEs for the SST k-\u03c9 and the RNG k-\u03b5 models are 0.0106 and 0.0117, respectively. In comparison, the MAE for the Realizable k-\u03b5 model and SA model are 0.0241 and 0.0228, respectively, which are almost twice as large as the RNG k-\u03b5 and the SST k-\u03c9 model. Therefore, the RNG k-\u03b5 model is utilized in this study.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " compares the four numerical models\u2019 mean average values (MAE). The results indicate that the MAEs for the SA and Realizable k-\u03b5 models are larger than the SST k-\u03c9 and RNG k-\u03b5 models. Furthermore, the trend of the RNG k-\u03b5 model results matched better with the data obtained from the experiments. The MAEs for the SST k-\u03c9 and the RNG k-\u03b5 models are 0.0106 and 0.0117, respectively. In comparison, the MAE for the Realizable k-\u03b5 model and SA model are 0.0241 and 0.0228, respectively, which are almost twice as large as the RNG k-\u03b5 and the SST k-\u03c9 model. 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The y+ value for the near-wall cell is 1. Moreover, the grid stretch ratio is measured as 1.2 away from the solid wall. The grid cell number must be determined carefully since a massive number of grid cells raises the computational time meaninglessly, while too limited cell number conveys limited temperature distribution information and causes inaccuracy (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "In this study, the unstructured hybrid mesh is utilized. The y+ value for the near-wall cell is 1. Moreover, the grid stretch ratio is measured as 1.2 away from the solid wall. The grid cell number must be determined carefully since a massive number of grid cells raises the computational time meaninglessly, while too limited cell number conveys limited temperature distribution information and causes inaccuracy ("}}]}, "properties": [], "parentId": "276", "childIds": [], "backendDOMNodeId": 2908}, {"nodeId": "944", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "34", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "34"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "276", "childIds": ["1950"], "backendDOMNodeId": 2909, "browsergym_id": "0c0e6cad-3a76-4450"}, {"nodeId": "945", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ", ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", "}}]}, "properties": [], "parentId": "276", "childIds": [], "backendDOMNodeId": 2911}, {"nodeId": "946", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "35", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "35"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "276", "childIds": ["1951"], "backendDOMNodeId": 2912, "browsergym_id": "5f050d67-49b4-4989"}, {"nodeId": "947", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "). Therefore, the 2, 4.5, 6, and 7.5 million grid sizes are studied on the centerline of the flat plate model. The result is shown in ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "). Therefore, the 2, 4.5, 6, and 7.5 million grid sizes are studied on the centerline of the flat plate model. 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The 7.5 million grid cell case has the most significant fluctuation among all, which implies that the 7.5-million case is the most sensitive to react. This paper sets the grid cell number at a 6-million grid size for analyzing training and validation CFD data. ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "When the location is right downstream of the coolant hole, the 2-million case obviously differs from 4.5, 6, and 7.5-million cases, whereas the difference narrows as the distance increases. The 7.5 million grid cell case has the most significant fluctuation among all, which implies that the 7.5-million case is the most sensitive to react. This paper sets the grid cell number at a 6-million grid size for analyzing training and validation CFD data. "}}]}, "properties": [], "parentId": "282", "childIds": [], "backendDOMNodeId": 2931}, {"nodeId": "954", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 4", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 4"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "282", "childIds": ["1956"], "backendDOMNodeId": 2932, "browsergym_id": "5350fca6-b5f7-4a14"}, {"nodeId": "955", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " is the mesh schematic from three views: Axonometric, Front, and Top. It can be observed that a more accurate mesh resolution is located near the coolant hole.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " is the mesh schematic from three views: Axonometric, Front, and Top. 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The input is a matrix containing coolant tube diameter, coolant tube inclination angle, density ratio, and blowing ratio. The output is a ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "Given the enormous computational amount of the CFD method, this paper adopts ANN to reduce the computational burden. The input is a matrix containing coolant tube diameter, coolant tube inclination angle, density ratio, and blowing ratio. The output is a "}}]}, "properties": [], "parentId": "291", "childIds": [], "backendDOMNodeId": 2953}, {"nodeId": "962", "ignored": false, "role": {"type": "role", "value": "generic"}, "chromeRole": {"type": "internalRole", "value": 88}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "291", "childIds": ["1960", "1961"], "backendDOMNodeId": 2954, "browsergym_id": "c4261a8a-4881-4dc7"}, {"nodeId": "963", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "-dimensional matrix, with each entry representing the grid\u2019s temperature at the flat plate model\u2019s external surface. Cooling effectiveness can thus be obtained from this output matrix by applying Eqs ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "-dimensional matrix, with each entry representing the grid\u2019s temperature at the flat plate model\u2019s external surface. 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The input data are normalized within (0, 1) before plugging into the input matrix. In Eq. ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ". The input data are normalized within (0, 1) before plugging into the input matrix. In Eq. 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The ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", respectively. The "}}]}, "properties": [], "parentId": "296", "childIds": [], "backendDOMNodeId": 3947}, {"nodeId": "1000", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "296", "childIds": ["1982"], "backendDOMNodeId": 3948, "browsergym_id": "64e86ad7-2065-4564"}, {"nodeId": "1001", "ignored": false, "role": {"type": "role", "value": "subscript"}, "chromeRole": {"type": "internalRole", "value": 185}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "296", "childIds": ["1983"], "backendDOMNodeId": 3950, "browsergym_id": "76725e18-d926-4dd6"}, {"nodeId": "1002", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " denotes the output of the 2nd, 3rd, 4th, 5th, and 6th layers. Equation ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " denotes the output of the 2nd, 3rd, 4th, 5th, and 6th layers. Equation "}}]}, "properties": [], "parentId": "296", "childIds": [], "backendDOMNodeId": 3953}, {"nodeId": "1003", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "11", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "11"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "296", "childIds": ["1984"], "backendDOMNodeId": 3954, "browsergym_id": "f913cc45-34b9-4917"}, {"nodeId": "1004", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " shows the forward propagation in the output layer. The ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " shows the forward propagation in the output layer. The "}}]}, "properties": [], "parentId": "296", "childIds": [], "backendDOMNodeId": 3956}, {"nodeId": "1005", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "296", "childIds": ["1985"], "backendDOMNodeId": 3957, "browsergym_id": "4a306944-5e64-4d43"}, {"nodeId": "1006", "ignored": false, "role": {"type": "role", "value": "subscript"}, "chromeRole": {"type": "internalRole", "value": 185}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "296", "childIds": ["1986"], "backendDOMNodeId": 3959, "browsergym_id": "4437233d-6081-410e"}, {"nodeId": "1007", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " stands for the output layer. In the output layer, final weighting and biasing are implemented. Then the result will be plugged into a sigmoid function to generate the predicted temperature distribution as the output value.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " stands for the output layer. In the output layer, final weighting and biasing are implemented. Then the result will be plugged into a sigmoid function to generate the predicted temperature distribution as the output value."}}]}, "properties": [], "parentId": "296", "childIds": [], "backendDOMNodeId": 3962}, {"nodeId": "1008", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "Batch normalization and dropout are implemented in the five hidden layers to enhance learning and avoid the neural network collapsing by big data. Mean square error (MSE) is deployed as a loss function to assess the difference between predicted temperature ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "Batch normalization and dropout are implemented in the five hidden layers to enhance learning and avoid the neural network collapsing by big data. Mean square error (MSE) is deployed as a loss function to assess the difference between predicted temperature "}}]}, "properties": [], "parentId": "297", "childIds": [], "backendDOMNodeId": 3964}, {"nodeId": "1009", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "297", "childIds": ["1987"], "backendDOMNodeId": 3965, "browsergym_id": "f49ce902-4f3b-459c"}, {"nodeId": "1010", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " and the CFD simulated value ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " and the CFD simulated value "}}]}, "properties": [], "parentId": "297", "childIds": [], "backendDOMNodeId": 3967}, {"nodeId": "1011", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "297", "childIds": ["1988"], "backendDOMNodeId": 3968, "browsergym_id": "da107416-ca60-41a3"}, {"nodeId": "1012", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ", as shown in Eq. ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", as shown in Eq. "}}]}, "properties": [], "parentId": "297", "childIds": [], "backendDOMNodeId": 3970}, {"nodeId": "1013", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "12", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "12"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "297", "childIds": ["1989"], "backendDOMNodeId": 3971, "browsergym_id": "ae73a519-2fa1-43b2"}, {"nodeId": "1014", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ". The dropout is set to 0.1 in case of overfitting. The regression starts from 4 neurons and then multiplies until 256 neurons in the output layer. ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ". The dropout is set to 0.1 in case of overfitting. The regression starts from 4 neurons and then multiplies until 256 neurons in the output layer. 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Validation", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "Training and Validation"}}]}, "properties": [], "parentId": "307", "childIds": [], "backendDOMNodeId": 4518}, {"nodeId": "1030", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "In the training process, the learning rate is one of the most significant hyperparameters that needs to be determined when applying ANN (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "In the training process, the learning rate is one of the most significant hyperparameters that needs to be determined when applying ANN ("}}]}, "properties": [], "parentId": "308", "childIds": [], "backendDOMNodeId": 4520}, {"nodeId": "1031", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": 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In this study, the learning rate is set to 0.01, and it is reset to 10% of its former value after every 1,000 epochs to keep convergence. The MSE is used to be the error index to evaluate whether the convergence of the model is accomplished. ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "). In this study, the learning rate is set to 0.01, and it is reset to 10% of its former value after every 1,000 epochs to keep convergence. The MSE is used to be the error index to evaluate whether the convergence of the model is accomplished. "}}]}, "properties": [], "parentId": "308", "childIds": [], "backendDOMNodeId": 4526}, {"nodeId": "1035", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 6", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 6"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "308", "childIds": ["2005"], "backendDOMNodeId": 4527, "browsergym_id": "81b6c806-7a35-4dee"}, {"nodeId": "1036", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " shows that as the number of epochs increases, the MSE value converges. There is a noticeable fluctuation before the epoch reaches around 500. However, with the continuous growth of epochs, the value of MSE and the fluctuation keep falling.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " shows that as the number of epochs increases, the MSE value converges. There is a noticeable fluctuation before the epoch reaches around 500. However, with the continuous growth of epochs, the value of MSE and the fluctuation keep falling."}}]}, "properties": [], "parentId": "308", "childIds": [], "backendDOMNodeId": 4529}, {"nodeId": "1037", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "FIGURE 6", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "FIGURE 6"}}]}, "properties": [], "parentId": "310", "childIds": [], "backendDOMNodeId": 4532}, {"nodeId": "1038", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "www.frontiersin.org", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "www.frontiersin.org"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "311", "childIds": ["2006"], "backendDOMNodeId": 4534, "browsergym_id": "1d60e389-fc80-4308"}, {"nodeId": "1039", "ignored": false, "role": {"type": "role", "value": "paragraph"}, "chromeRole": {"type": "internalRole", "value": 133}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "311", "childIds": ["2007", "2008"], "backendDOMNodeId": 4536, "browsergym_id": "7d948511-2923-4c2c"}, {"nodeId": "1040", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "According to the result, the 0.01 learning rate and reduction to 10% of its last value every 1,000 epochs is a good choice. Quoted error (QE) is proposed in Eq. ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "According to the result, the 0.01 learning rate and reduction to 10% of its last value every 1,000 epochs is a good choice. Quoted error (QE) is proposed in Eq. "}}]}, "properties": [], "parentId": "314", "childIds": [], "backendDOMNodeId": 4543}, {"nodeId": "1041", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "13", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "13"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "314", "childIds": ["2009"], "backendDOMNodeId": 4544, "browsergym_id": "2023f9f2-1e83-4e0d"}, {"nodeId": "1042", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " to measure the ANN model\u2019s absolute error. QE also serves as an index to help find the optimal hyperparameter settings. In the expression of QE, ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " to measure the ANN model\u2019s absolute error. QE also serves as an index to help find the optimal hyperparameter settings. In the expression of QE, "}}]}, "properties": [], "parentId": "314", "childIds": [], "backendDOMNodeId": 4546}, {"nodeId": "1043", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "314", "childIds": ["2010"], "backendDOMNodeId": 4547, "browsergym_id": "1fab6434-3c6c-46ad"}, {"nodeId": "1044", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " is the temperature derived from CFD simulation, and ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " is the temperature derived from CFD simulation, and "}}]}, "properties": [], "parentId": "314", "childIds": [], "backendDOMNodeId": 4549}, {"nodeId": "1045", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "314", "childIds": ["2011"], "backendDOMNodeId": 4550, "browsergym_id": "4a2a40d7-9e52-4810"}, {"nodeId": "1046", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " is the predicted temperature result at the final layer of the ANN. ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " is the predicted temperature result at the final layer of the ANN. "}}]}, "properties": [], "parentId": "314", "childIds": [], "backendDOMNodeId": 4552}, {"nodeId": "1047", "ignored": false, "role": {"type": "role", "value": "generic"}, "chromeRole": {"type": "internalRole", "value": 88}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "314", "childIds": ["2012", "2013"], "backendDOMNodeId": 4553, "browsergym_id": "3279b388-8224-4bed"}, {"nodeId": "1048", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " is a fixed number 0, and the upper bound of ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " is a fixed number 0, and the upper bound of "}}]}, "properties": [], "parentId": "314", "childIds": [], "backendDOMNodeId": 4591}, {"nodeId": "1049", "ignored": false, "role": {"type": "role", "value": "generic"}, "chromeRole": {"type": "internalRole", "value": 88}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "314", "childIds": ["2014", "2015"], "backendDOMNodeId": 4592, "browsergym_id": "0b495bfd-bcfd-4263"}, {"nodeId": "1050", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ". The result is scaled to a hundred percent of the corresponding QE value.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ". The result is scaled to a hundred percent of the corresponding QE value."}}]}, "properties": [], "parentId": "314", "childIds": [], "backendDOMNodeId": 4646}, {"nodeId": "1051", "ignored": true, "ignoredReasons": [{"name": "notRendered", "value": {"type": "boolean", "value": true}}], "role": {"type": "role", "value": "none"}, "chromeRole": {"type": "internalRole", "value": 0}, "parentId": "315", "childIds": [], "backendDOMNodeId": 4648}, {"nodeId": "1052", "ignored": false, "role": {"type": "role", "value": "generic"}, "chromeRole": {"type": "internalRole", "value": 88}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents"}, {"type": "attribute", "attribute": "title"}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "315", "childIds": ["2016", "2018"], "backendDOMNodeId": 4649}, {"nodeId": "1053", "ignored": false, "role": {"type": "role", "value": "generic"}, "chromeRole": {"type": "internalRole", "value": 88}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "315", "childIds": [], "backendDOMNodeId": 4802, "browsergym_id": "816f9ab6-b5f8-4161"}, {"nodeId": "1054", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "The ANN model uses QE to find the optimized hyperparameter settings containing splitting ratio, dropout, and batch size. The splitting ratio is acquired by dividing the amount of validation dataset by the whole dataset. A higher splitting ratio means a relatively lower portion of data is utilized in the training process. Thus, a balance in training and validation must be determined to achieve better prediction efficiency and accuracy. An experiment aiming at finding the optimal splitting ratio is conducted, and the result is shown in ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "The ANN model uses QE to find the optimized hyperparameter settings containing splitting ratio, dropout, and batch size. The splitting ratio is acquired by dividing the amount of validation dataset by the whole dataset. A higher splitting ratio means a relatively lower portion of data is utilized in the training process. Thus, a balance in training and validation must be determined to achieve better prediction efficiency and accuracy. An experiment aiming at finding the optimal splitting ratio is conducted, and the result is shown in "}}]}, "properties": [], "parentId": "316", "childIds": [], "backendDOMNodeId": 4804}, {"nodeId": "1055", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 7A", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 7A"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "316", "childIds": ["2019"], "backendDOMNodeId": 4805, "browsergym_id": "09c2234b-43ac-4754"}, {"nodeId": "1056", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ". The QE value of the case with splitting ratio = 0.2 is the highest compared with the situations whose splitting ratios are 0.1 and 0.3, which indicates that there is no simple proportional relationship between the magnitude of the error and the magnitude of splitting ratio. Besides, it is found that the QE value of the validation dataset is always higher than the training dataset by the ANN algorithm, regardless of which splitting ratio is chosen. Results show that a splitting ratio of 0.3 is believed to be the best among the three splitting ratios researched.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ". The QE value of the case with splitting ratio = 0.2 is the highest compared with the situations whose splitting ratios are 0.1 and 0.3, which indicates that there is no simple proportional relationship between the magnitude of the error and the magnitude of splitting ratio. Besides, it is found that the QE value of the validation dataset is always higher than the training dataset by the ANN algorithm, regardless of which splitting ratio is chosen. Results show that a splitting ratio of 0.3 is believed to be the best among the three splitting ratios researched."}}]}, "properties": [], "parentId": "316", "childIds": [], "backendDOMNodeId": 4807}, {"nodeId": "1057", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "FIGURE 7", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "FIGURE 7"}}]}, "properties": [], "parentId": "318", "childIds": [], "backendDOMNodeId": 4810}, {"nodeId": "1058", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "www.frontiersin.org", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "www.frontiersin.org"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "319", "childIds": ["2020"], "backendDOMNodeId": 4812, "browsergym_id": "55450316-06ee-4374"}, {"nodeId": "1059", "ignored": false, "role": {"type": "role", "value": "paragraph"}, "chromeRole": {"type": "internalRole", "value": 133}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "319", "childIds": ["2021", "2022", "2023", "2024", "2025", "2026", "2027", "2028", "2029", "2030"], "backendDOMNodeId": 4814, "browsergym_id": "88e1e3a0-73c0-4e60"}, {"nodeId": "1060", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "Similar experiments are designed for dropout and batch size. ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "Similar experiments are designed for dropout and batch size. "}}]}, "properties": [], "parentId": "322", "childIds": [], "backendDOMNodeId": 4833}, {"nodeId": "1061", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 7B", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 7B"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "322", "childIds": ["2031"], "backendDOMNodeId": 4834, "browsergym_id": "22ffe37b-f576-48ad"}, {"nodeId": "1062", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " is the result of finding the ideal dropout. There is an apparent disparity between the case where the dropout is 0.1 compared to cases with 0.2 and 0.3 dropouts. The QE for the training dataset with 0.1 dropout is 0.31%, and the QE for the validation dataset with 0.1 dropouts is 0.33%. The QEs for the other two cases vary from 0.52% to 0.55%, which are much larger than those with a dropout of 0.1. This proves that the case with a dropout of 0.1 has the least error between the predicted temperature and the simulated value.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " is the result of finding the ideal dropout. There is an apparent disparity between the case where the dropout is 0.1 compared to cases with 0.2 and 0.3 dropouts. The QE for the training dataset with 0.1 dropout is 0.31%, and the QE for the validation dataset with 0.1 dropouts is 0.33%. The QEs for the other two cases vary from 0.52% to 0.55%, which are much larger than those with a dropout of 0.1. This proves that the case with a dropout of 0.1 has the least error between the predicted temperature and the simulated value."}}]}, "properties": [], "parentId": "322", "childIds": [], "backendDOMNodeId": 4836}, {"nodeId": "1063", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "For Batch size, three different batch sizes are studied, and ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "For Batch size, three different batch sizes are studied, and "}}]}, "properties": [], "parentId": "323", "childIds": [], "backendDOMNodeId": 4838}, {"nodeId": "1064", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 7C", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 7C"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "323", "childIds": ["2032"], "backendDOMNodeId": 4839, "browsergym_id": "8bf95591-d47d-4d78"}, {"nodeId": "1065", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " plots the result. The QE values of three different batch sizes are all located at [0.31%,0.38%], which implies that the batch size does not serve as a significant parameter with a considerable influence on the output in the ANN model. In the case with 32 batch size, the MSEs for the validation and training datasets are 0.33% and 0.31%, respectively. Therefore, the optimal batch size of 32 is chosen. For learning rate, as shown in ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " plots the result. The QE values of three different batch sizes are all located at [0.31%,0.38%], which implies that the batch size does not serve as a significant parameter with a considerable influence on the output in the ANN model. In the case with 32 batch size, the MSEs for the validation and training datasets are 0.33% and 0.31%, respectively. Therefore, the optimal batch size of 32 is chosen. For learning rate, as shown in "}}]}, "properties": [], "parentId": "323", "childIds": [], "backendDOMNodeId": 4841}, {"nodeId": "1066", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 7D", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 7D"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "323", "childIds": ["2033"], "backendDOMNodeId": 4842, "browsergym_id": "101e8d94-a84f-42c1"}, {"nodeId": "1067", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ", it is easily found that the varied learning rate could provide the best performance over the fixed learning rate such as 0.01, 0.001, and 0.0001. In all, the optimal hyperparameters are: dropout = 0.1, batch size = 32, splitting ratio = 0.3, and a varied learning rate.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", it is easily found that the varied learning rate could provide the best performance over the fixed learning rate such as 0.01, 0.001, and 0.0001. In all, the optimal hyperparameters are: dropout = 0.1, batch size = 32, splitting ratio = 0.3, and a varied learning rate."}}]}, "properties": [], "parentId": "323", "childIds": [], "backendDOMNodeId": 4844}, {"nodeId": "1068", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "Moreover, the structure of the ANN has been investigated to obtain the best performance. With these optimal parameters, the number of layers is determined to be 7 and the modes are determined according to the symmetry aiming for best training results. The information of different layers and nodes selection is shown in ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "Moreover, the structure of the ANN has been investigated to obtain the best performance. With these optimal parameters, the number of layers is determined to be 7 and the modes are determined according to the symmetry aiming for best training results. The information of different layers and nodes selection is shown in "}}]}, "properties": [], "parentId": "324", "childIds": [], "backendDOMNodeId": 4846}, {"nodeId": "1069", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Table 2", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Table 2"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "324", "childIds": ["2034"], "backendDOMNodeId": 4847, "browsergym_id": "3a5ebb11-4b92-4053"}, {"nodeId": "1070", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " below. We chose 2, 3, 4, 7, and 9 layers because under these cases, the nodes arrangements are symmetric from 4 nodes to 256 nodes. In the experiment, we find that when the layer number comes to 7, the quoted error value (QE) reaches its minimum. However, we find that the quoted value of the 9-layer case increases, which is because too much layer increases the number of parameters and the iteration error. In the process of training, it is also reasonable in practice that some parameters are lost. After comparison, we find that the QE value of the 7-layer case is quite acceptable, so we consider 7 layers as the best layer number choice.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " below. We chose 2, 3, 4, 7, and 9 layers because under these cases, the nodes arrangements are symmetric from 4 nodes to 256 nodes. In the experiment, we find that when the layer number comes to 7, the quoted error value (QE) reaches its minimum. However, we find that the quoted value of the 9-layer case increases, which is because too much layer increases the number of parameters and the iteration error. In the process of training, it is also reasonable in practice that some parameters are lost. After comparison, we find that the QE value of the 7-layer case is quite acceptable, so we consider 7 layers as the best layer number choice."}}]}, "properties": [], "parentId": "324", "childIds": [], "backendDOMNodeId": 4849}, {"nodeId": "1071", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "TABLE 2", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "TABLE 2"}}]}, "properties": [], "parentId": "326", "childIds": [], "backendDOMNodeId": 4852}, {"nodeId": "1072", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "www.frontiersin.org", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "www.frontiersin.org"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "327", "childIds": ["2035"], "backendDOMNodeId": 4854, "browsergym_id": "479743de-4039-4cbc"}, {"nodeId": "1073", "ignored": false, "role": {"type": "role", "value": "paragraph"}, "chromeRole": {"type": "internalRole", "value": 133}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "327", "childIds": ["2036", "2037"], "backendDOMNodeId": 4856, "browsergym_id": "a67cb980-4b7c-4478"}, {"nodeId": "1074", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "To further visualize the prediction accuracy using the designed ANN model, the fixed-cord-averaged film cooling effectiveness achieved by the ANN and CFD method simulation are compared for training and validation datasets. Six cases with diverse input parameter sets containing ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "To further visualize the prediction accuracy using the designed ANN model, the fixed-cord-averaged film cooling effectiveness achieved by the ANN and CFD method simulation are compared for training and validation datasets. Six cases with diverse input parameter sets containing "}}]}, "properties": [], "parentId": "330", "childIds": [], "backendDOMNodeId": 4863}, {"nodeId": "1075", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "330", "childIds": ["2038"], "backendDOMNodeId": 4864, "browsergym_id": "20d11cee-f5a2-4a69"}, {"nodeId": "1076", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ", ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", "}}]}, "properties": [], "parentId": "330", "childIds": [], "backendDOMNodeId": 4866}, {"nodeId": "1077", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "330", "childIds": ["2039"], "backendDOMNodeId": 4867, "browsergym_id": "ec718f42-de1c-447c"}, {"nodeId": "1078", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ", ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", "}}]}, "properties": [], "parentId": "330", "childIds": [], "backendDOMNodeId": 4869}, {"nodeId": "1079", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "330", "childIds": ["2040"], "backendDOMNodeId": 4870, "browsergym_id": "c61ad685-03db-4756"}, {"nodeId": "1080", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ", and ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", and "}}]}, "properties": [], "parentId": "330", "childIds": [], "backendDOMNodeId": 4872}, {"nodeId": "1081", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "330", "childIds": ["2041"], "backendDOMNodeId": 4873, "browsergym_id": "d278a4b1-3a83-48e0"}, {"nodeId": "1082", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " are randomly selected. The fixed-cord-averaged film cooling effectiveness on the upper surface of the turbine blade under six different cases are shown in ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " are randomly selected. The fixed-cord-averaged film cooling effectiveness on the upper surface of the turbine blade under six different cases are shown in "}}]}, "properties": [], "parentId": "330", "childIds": [], "backendDOMNodeId": 4875}, {"nodeId": "1083", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 8", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 8"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "330", "childIds": ["2042"], "backendDOMNodeId": 4876, "browsergym_id": "bf8901dd-98e3-4733"}, {"nodeId": "1084", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ". All the six plots in ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ". All the six plots in "}}]}, "properties": [], "parentId": "330", "childIds": [], "backendDOMNodeId": 4878}, {"nodeId": "1085", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 8", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 8"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "330", "childIds": ["2043"], "backendDOMNodeId": 4879, "browsergym_id": "2c3cd94c-fd5c-4201"}, {"nodeId": "1086", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " are about the fixed-cord-averaged cooling effectiveness results. The blue dotted lines in the plots represent the CFD cooling results, while the red line indicates the ANN results.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " are about the fixed-cord-averaged cooling effectiveness results. The blue dotted lines in the plots represent the CFD cooling results, while the red line indicates the ANN results."}}]}, "properties": [], "parentId": "330", "childIds": [], "backendDOMNodeId": 4881}, {"nodeId": "1087", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "FIGURE 8", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "FIGURE 8"}}]}, "properties": [], "parentId": "332", "childIds": [], "backendDOMNodeId": 4884}, {"nodeId": "1088", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "www.frontiersin.org", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "www.frontiersin.org"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "333", "childIds": ["2044"], "backendDOMNodeId": 4886, "browsergym_id": "f98a4156-7096-46d8"}, {"nodeId": "1089", "ignored": false, "role": {"type": "role", "value": "paragraph"}, "chromeRole": {"type": "internalRole", "value": 133}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "333", "childIds": ["2045", "2046", "2047", "2048", "2049", "2050"], "backendDOMNodeId": 4888, "browsergym_id": "f05b6c71-e865-4fc0"}, {"nodeId": "1090", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 8A", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 8A"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "336", "childIds": ["2051"], "backendDOMNodeId": 4901, "browsergym_id": "c1c96418-630c-4c2e"}, {"nodeId": "1091", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " is for training datasets, and ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " is for training datasets, and "}}]}, "properties": [], "parentId": "336", "childIds": [], "backendDOMNodeId": 4903}, {"nodeId": "1092", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 8B", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 8B"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "336", "childIds": ["2052"], "backendDOMNodeId": 4904, "browsergym_id": "77251936-13ea-4b3b"}, {"nodeId": "1093", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " is for validation datasets. The result shows that the temperatures predicted using the ANN model for the training and validation datasets almost overlap with the temperatures obtained from CDF simulation. For example, in the case where ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " is for validation datasets. The result shows that the temperatures predicted using the ANN model for the training and validation datasets almost overlap with the temperatures obtained from CDF simulation. 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While ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " is positive zero, compared with the result derived by the ANN model of 0.130. While "}}]}, "properties": [], "parentId": "336", "childIds": [], "backendDOMNodeId": 4945}, {"nodeId": "1106", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "336", "childIds": ["2061"], "backendDOMNodeId": 4946, "browsergym_id": "7bf8ff60-0840-416f"}, {"nodeId": "1107", "ignored": false, "role": {"type": "role", "value": "subscript"}, "chromeRole": {"type": "internalRole", "value": 185}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "336", "childIds": ["2062"], "backendDOMNodeId": 4948, "browsergym_id": "b870de61-398c-4dac"}, {"nodeId": "1108", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " increases up to 15, the two curves almost overlap, and the error is negligible. After ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " increases up to 15, the two curves almost overlap, and the error is negligible. After "}}]}, "properties": [], "parentId": "336", "childIds": [], "backendDOMNodeId": 4951}, {"nodeId": "1109", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "336", "childIds": ["2063"], "backendDOMNodeId": 4952, "browsergym_id": "822f15cd-f814-4ed2"}, {"nodeId": "1110", "ignored": false, "role": {"type": "role", "value": "subscript"}, "chromeRole": {"type": "internalRole", "value": 185}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "336", "childIds": ["2064"], "backendDOMNodeId": 4954, "browsergym_id": "19f8f898-8455-4a86"}, {"nodeId": "1111", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " goes beyond 15, the error expands to its maximum value of 4.28%, where ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " goes beyond 15, the error expands to its maximum value of 4.28%, where "}}]}, "properties": [], "parentId": "336", "childIds": [], "backendDOMNodeId": 4957}, {"nodeId": "1112", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "336", "childIds": ["2065"], "backendDOMNodeId": 4958, "browsergym_id": "e865bcb6-6cfc-4ccf"}, {"nodeId": "1113", "ignored": false, "role": {"type": "role", "value": "subscript"}, "chromeRole": {"type": "internalRole", "value": 185}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "336", "childIds": ["2066"], "backendDOMNodeId": 4960, "browsergym_id": "abe282e2-6dc3-4031"}, {"nodeId": "1114", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " equals 17.4. 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Then, as "}}]}, "properties": [], "parentId": "336", "childIds": [], "backendDOMNodeId": 4963}, {"nodeId": "1115", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "336", "childIds": ["2067"], "backendDOMNodeId": 4964, "browsergym_id": "7bade081-980f-4ece"}, {"nodeId": "1116", "ignored": false, "role": {"type": "role", "value": "subscript"}, "chromeRole": {"type": "internalRole", "value": 185}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "336", "childIds": ["2068"], "backendDOMNodeId": 4966, "browsergym_id": "8b333c73-d731-45fb"}, {"nodeId": "1117", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " keeps increasing, the error minimizes continuously. At the back end of the research region, the error is close to zero again. For fixed-cord-averaged film cooling effectiveness, the QE for training datasets is 0.29%, while for the validation dataset it is 0.32%. Conclusion can be drawn that even though fluctuation still occurs inevitably, the regression performance of the ANN model in fixed-cord-averaged film cooling effectiveness is delighted under all randomly selected cases.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " keeps increasing, the error minimizes continuously. At the back end of the research region, the error is close to zero again. For fixed-cord-averaged film cooling effectiveness, the QE for training datasets is 0.29%, while for the validation dataset it is 0.32%. Conclusion can be drawn that even though fluctuation still occurs inevitably, the regression performance of the ANN model in fixed-cord-averaged film cooling effectiveness is delighted under all randomly selected cases."}}]}, "properties": [], "parentId": "336", "childIds": [], "backendDOMNodeId": 4969}, {"nodeId": "1118", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "Besides the fixed-cord-averaged cooling effectiveness, the general cooling effectiveness is also studied to enhance the above conclusion. ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "Besides the fixed-cord-averaged cooling effectiveness, the general cooling effectiveness is also studied to enhance the above conclusion. "}}]}, "properties": [], "parentId": "337", "childIds": [], "backendDOMNodeId": 4971}, {"nodeId": "1119", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 9", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 9"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "337", "childIds": ["2069"], "backendDOMNodeId": 4972, "browsergym_id": "edd788f7-9832-46d5"}, {"nodeId": "1120", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " compares the overall film cooling effectiveness from CFD and ANN methods downstream the coolant hole. The relationship between general film cooling effectiveness and computation numbers is plotted in ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " compares the overall film cooling effectiveness from CFD and ANN methods downstream the coolant hole. The relationship between general film cooling effectiveness and computation numbers is plotted in "}}]}, "properties": [], "parentId": "337", "childIds": [], "backendDOMNodeId": 4974}, {"nodeId": "1121", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 9", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 9"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "337", "childIds": ["2070"], "backendDOMNodeId": 4975, "browsergym_id": "4b3deb14-4ace-4c7c"}, {"nodeId": "1122", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ". 225 (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ". 225 ("}}]}, "properties": [], "parentId": "337", "childIds": [], "backendDOMNodeId": 4977}, {"nodeId": "1123", "ignored": false, "role": {"type": "role", "value": "generic"}, "chromeRole": {"type": "internalRole", "value": 88}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "337", "childIds": ["2071", "2072"], "backendDOMNodeId": 4978, "browsergym_id": "e2d23e98-7001-45d9"}, {"nodeId": "1124", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ") cases of 0.3 splitting ratio are included, which means that ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ") cases of 0.3 splitting ratio are included, which means that "}}]}, "properties": [], "parentId": "337", "childIds": [], "backendDOMNodeId": 5022}, {"nodeId": "1125", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 9A", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 9A"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "337", "childIds": ["2073"], "backendDOMNodeId": 5023, "browsergym_id": "9da7212b-376c-483e"}, {"nodeId": "1126", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " includes the 156 training data, ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " includes the 156 training data, "}}]}, "properties": [], "parentId": "337", "childIds": [], "backendDOMNodeId": 5025}, {"nodeId": "1127", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 9B", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 9B"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "337", "childIds": ["2074"], "backendDOMNodeId": 5026, "browsergym_id": "f73e8d01-149d-4e38"}, {"nodeId": "1128", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " includes the 69 validation data. And they are ranked according to the magnitude of their general film cooling effectiveness to exhibit the results in a visual-friendly way. We labeled each data point using Computation No. from 1 to 156 and from 1 to 69 as shown on the horizontal axis. So, two lines are both discrete lines. Even though it is inevitable for the ANN and CFD results to have differences because the ANN\u2019s training data are derived from CFD. The results show that the general film cooling effectiveness derived from the ANN model is accurate enough for both training and validation data, regardless of the computation number. For general film cooling effectiveness, the QE for training datasets is 0.35%, while for the validation dataset, it is 0.30%.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " includes the 69 validation data. And they are ranked according to the magnitude of their general film cooling effectiveness to exhibit the results in a visual-friendly way. We labeled each data point using Computation No. from 1 to 156 and from 1 to 69 as shown on the horizontal axis. So, two lines are both discrete lines. Even though it is inevitable for the ANN and CFD results to have differences because the ANN\u2019s training data are derived from CFD. The results show that the general film cooling effectiveness derived from the ANN model is accurate enough for both training and validation data, regardless of the computation number. For general film cooling effectiveness, the QE for training datasets is 0.35%, while for the validation dataset, it is 0.30%."}}]}, "properties": [], "parentId": "337", "childIds": [], "backendDOMNodeId": 5028}, {"nodeId": "1129", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "FIGURE 9", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "FIGURE 9"}}]}, "properties": [], "parentId": "339", "childIds": [], "backendDOMNodeId": 5031}, {"nodeId": "1130", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "www.frontiersin.org", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "www.frontiersin.org"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "340", "childIds": ["2075"], "backendDOMNodeId": 5033, "browsergym_id": "0ca8b8ba-c037-49d9"}, {"nodeId": "1131", "ignored": false, "role": {"type": "role", "value": "paragraph"}, "chromeRole": {"type": "internalRole", "value": 133}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "340", "childIds": ["2076", "2077", "2078", "2079", "2080", "2081"], "backendDOMNodeId": 5035, "browsergym_id": "ceaa943d-4503-496c"}, {"nodeId": "1132", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "Uncertainty Analysis", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "Uncertainty Analysis"}}]}, "properties": [], "parentId": "344", "childIds": [], "backendDOMNodeId": 5049}, {"nodeId": "1133", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "Monte Carlo Simulation and Sample Size", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "Monte Carlo Simulation and Sample Size"}}]}, "properties": [], "parentId": "345", "childIds": [], "backendDOMNodeId": 5051}, {"nodeId": "1134", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "As the designing and manufacturing processes are deterministic, the variety of structures is usually not considered. 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simulation is an extensively utilized technique to quantify the engineering field\u2019s uncertainty among various kinds of uncertainty quantification methods ("}}]}, "properties": [], "parentId": "347", "childIds": [], "backendDOMNodeId": 5073}, {"nodeId": "1148", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "40", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "40"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "347", "childIds": ["2088"], "backendDOMNodeId": 5074, "browsergym_id": "8a3e57f6-1751-465d"}, {"nodeId": "1149", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, 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MC simulation conducts statistical analysis to sample datasets obtained by repeated random sampling (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "). MC simulation conducts statistical analysis to sample datasets obtained by repeated random sampling ("}}]}, "properties": [], "parentId": "347", "childIds": [], "backendDOMNodeId": 5076}, {"nodeId": "1150", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "41", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "41"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "347", "childIds": ["2089"], "backendDOMNodeId": 5077, "browsergym_id": "02555909-8ac3-4743"}, {"nodeId": "1151", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "). MC simulation shows excellent advantage in mathematics and engineering due to its concise methodology, broad application domain, and various software choices (", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "). MC simulation shows excellent advantage in mathematics and engineering due to its concise methodology, broad application domain, and various software choices ("}}]}, "properties": [], "parentId": "347", "childIds": [], "backendDOMNodeId": 5079}, {"nodeId": "1152", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "38", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "38"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "347", "childIds": ["2090"], "backendDOMNodeId": 5080, "browsergym_id": "2b30276a-e4ef-4b93"}, {"nodeId": "1153", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "). The mean and standard deviation of the mean squared pure error (MSPE), namely ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "). The mean and standard deviation of the mean squared pure error (MSPE), namely "}}]}, "properties": [], "parentId": "347", "childIds": [], "backendDOMNodeId": 5082}, {"nodeId": "1154", "ignored": false, "role": {"type": "role", "value": "generic"}, "chromeRole": {"type": "internalRole", "value": 88}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "347", "childIds": ["2091", "2092"], "backendDOMNodeId": 5083, "browsergym_id": "523c7403-8eae-4406"}, {"nodeId": "1155", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " are studied instead to impair its harmful effect. The random samples are generated in the following way: Firstly, a sample vector ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " are studied instead to impair its harmful effect. The random samples are generated in the following way: Firstly, a sample vector "}}]}, "properties": [], "parentId": "347", "childIds": [], "backendDOMNodeId": 5186}, {"nodeId": "1156", "ignored": false, "role": {"type": "role", "value": "generic"}, "chromeRole": {"type": "internalRole", "value": 88}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "347", "childIds": ["2093", "2094"], "backendDOMNodeId": 5187, "browsergym_id": "3fcc9c2b-3c45-4855"}, {"nodeId": "1157", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " is formed from the normalized training dataset, which is ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " is formed 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Secondly, enough sample vectors ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ". Secondly, enough sample vectors "}}]}, "properties": [], "parentId": "347", "childIds": [], "backendDOMNodeId": 5267}, {"nodeId": "1170", "ignored": false, "role": {"type": "role", "value": "generic"}, "chromeRole": {"type": "internalRole", "value": 88}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "347", "childIds": ["2102", "2103"], "backendDOMNodeId": 5268, "browsergym_id": "c69119a1-55d7-4531"}, {"nodeId": "1171", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " are generated in the same way and are arranged to form a distribution ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " are generated in the same way and are arranged to form a distribution "}}]}, "properties": [], "parentId": "347", "childIds": [], "backendDOMNodeId": 5300}, {"nodeId": "1172", "ignored": false, "role": {"type": "role", "value": "generic"}, "chromeRole": {"type": "internalRole", "value": 88}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "347", "childIds": ["2104"], "backendDOMNodeId": 5301, "browsergym_id": "9296a683-7ead-495b"}, {"nodeId": "1173", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " for the following MC simulation. The sample size is defined as the number of sample vectors in each distribution. Therefore, parallel experiments are conducted, and the MSPE is proposed to quantify how well the MC simulation behaves. The mean and the standard of MSPE are defined in Eq. ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " for the following MC simulation. The sample size is defined as the number of sample vectors in each distribution. Therefore, parallel experiments are conducted, and the MSPE is proposed to quantify how well the MC simulation behaves. The mean and the standard of MSPE are defined in Eq. 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The experiment results are shown in ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ". The experiment results are shown in "}}]}, "properties": [], "parentId": "347", "childIds": [], "backendDOMNodeId": 5307}, {"nodeId": "1176", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 10", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 10"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "347", "childIds": ["2106"], "backendDOMNodeId": 5308, "browsergym_id": "c0787f0f-fb6b-4226"}, {"nodeId": "1177", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ". It can be observed that even though the ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ". It can be observed that even though the "}}]}, "properties": [], "parentId": "347", "childIds": [], "backendDOMNodeId": 5310}, {"nodeId": "1178", "ignored": false, "role": {"type": "role", "value": "generic"}, "chromeRole": {"type": "internalRole", "value": 88}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "347", "childIds": ["2107", "2108"], "backendDOMNodeId": 5311, "browsergym_id": "8aa24558-e0cf-4b75"}, {"nodeId": "1179", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " almost remain at a steady level, when the sample size is below 10,000, the fluctuation of both ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " almost remain at a steady level, when the sample size is below 10,000, the fluctuation of both "}}]}, "properties": [], "parentId": "347", "childIds": [], "backendDOMNodeId": 5414}, {"nodeId": "1180", "ignored": false, "role": {"type": "role", "value": "generic"}, "chromeRole": {"type": "internalRole", "value": 88}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "347", "childIds": ["2109", "2110"], "backendDOMNodeId": 5415, "browsergym_id": "a8116979-9932-4997"}, {"nodeId": "1181", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " are very large, which represents that a sample size smaller than 10,000 is not suitable for MC simulation. 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If the blade surface is well covered by the cooling jet, its life span and reliability could be extended and increased heavily. To set up computation, the Probability Distribution Function (PDF) is introduced to represent the distribution of cooling effectiveness of every grid point on the flat surface of the turbine blade. The PDF are defined in Eq. ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", the temperature distribution near the blade also needs attention. If the blade surface is well covered by the cooling jet, its life span and reliability could be extended and increased heavily. To set up computation, the Probability Distribution Function (PDF) is introduced to represent the distribution of cooling effectiveness of every grid point on the flat surface of the turbine blade. The PDF are defined in Eq. 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It means that among the three geometric parameters, the deviation of coolant hole diameter has the largest uncertainty influence on the global film cooling effectiveness at a low blowing ratio. Followed by the hole diameter is the coolant jet inclination angle. Regardless of ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ". It means that among the three geometric parameters, the deviation of coolant hole diameter has the largest uncertainty influence on the global film cooling effectiveness at a low blowing ratio. Followed by the hole diameter is the coolant jet inclination angle. 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The coolant hole inclination angle is still the primary parameter, but its Sobol index is furthermore prominent than the medium-blowing ratio case. This time, the first-order and overall Sobol indices for ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " indicates that for a large blowing ratio of 1.5, the corresponding result can be interpreted as a magnified one of a blowing ratio of 1.0. The coolant hole inclination angle is still the primary parameter, but its Sobol index is furthermore prominent than the medium-blowing ratio case. This time, the first-order and overall Sobol indices for "}}]}, "properties": [], "parentId": "372", "childIds": [], "backendDOMNodeId": 8840}, {"nodeId": "1348", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "372", "childIds": ["2245"], "backendDOMNodeId": 8841, "browsergym_id": "791df718-dc0b-465f"}, {"nodeId": "1349", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " outstrip 95%. Compared with the Sobol indices under the medium blowing ratio ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " outstrip 95%. Compared with the Sobol indices under the medium blowing ratio "}}]}, "properties": [], "parentId": "372", "childIds": [], "backendDOMNodeId": 8843}, {"nodeId": "1350", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "372", "childIds": ["2246"], "backendDOMNodeId": 8844, "browsergym_id": "2645b91f-000b-413f"}, {"nodeId": "1351", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ", the hole diameter ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", the hole diameter "}}]}, "properties": [], "parentId": "372", "childIds": [], "backendDOMNodeId": 8846}, {"nodeId": "1352", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "372", "childIds": ["2247"], "backendDOMNodeId": 8847, "browsergym_id": "7c25ab76-05e3-4ca4"}, {"nodeId": "1353", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " and density ratio ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " and density ratio "}}]}, "properties": [], "parentId": "372", "childIds": [], "backendDOMNodeId": 8849}, {"nodeId": "1354", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "372", "childIds": ["2248"], "backendDOMNodeId": 8850, "browsergym_id": "907e14d9-2ed0-4529"}, {"nodeId": "1355", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ", which are all less than 3%, show negligible influence on the general cooling effectiveness. Moreover, it is found that when the blowing ratio increases, the ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", which are all less than 3%, show negligible influence on the general cooling effectiveness. Moreover, it is found that when the blowing ratio increases, the "}}]}, "properties": [], "parentId": "372", "childIds": [], "backendDOMNodeId": 8852}, {"nodeId": "1356", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "372", "childIds": ["2249"], "backendDOMNodeId": 8853, "browsergym_id": "96f9183a-8050-4618"}, {"nodeId": "1357", "ignored": false, "role": {"type": "role", "value": "subscript"}, "chromeRole": {"type": "internalRole", "value": 185}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "372", "childIds": ["2250"], "backendDOMNodeId": 8855, "browsergym_id": "774a05ef-6c92-4da8"}, {"nodeId": "1358", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " and ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " and "}}]}, "properties": [], "parentId": "372", "childIds": [], "backendDOMNodeId": 8858}, {"nodeId": "1359", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "372", "childIds": ["2251"], "backendDOMNodeId": 8859, "browsergym_id": "c815923e-f206-42eb"}, {"nodeId": "1360", "ignored": false, "role": {"type": "role", "value": "subscript"}, "chromeRole": {"type": "internalRole", "value": 185}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "372", "childIds": ["2252"], "backendDOMNodeId": 8861, "browsergym_id": "187501e9-16b2-42ab"}, {"nodeId": "1361", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " for all parameters increase accordingly.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " for all parameters increase accordingly."}}]}, "properties": [], "parentId": "372", "childIds": [], "backendDOMNodeId": 8864}, {"nodeId": "1362", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "In the gas turbine application, in a low blowing ratio case, both the coolant hole diameter and inclination angle significantly impact cooling effectiveness. However, the uncertain deviation of coolant hole diameter has a more significant effect. As for a high blowing ratio, usually more than 1.5, the coolant hole inclination angle needs special attention. In medium and high blowing ratio cases, the coolant inclination angle dominates the results, and its dominant effect increases as the blowing ratio increases, in all three cases. The trends of the first-order and the total-effect index are very similar. Thus, the same conclusion can be drawn.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "In the gas turbine application, in a low blowing ratio case, both the coolant hole diameter and inclination angle significantly impact cooling effectiveness. However, the uncertain deviation of coolant hole diameter has a more significant effect. As for a high blowing ratio, usually more than 1.5, the coolant hole inclination angle needs special attention. In medium and high blowing ratio cases, the coolant inclination angle dominates the results, and its dominant effect increases as the blowing ratio increases, in all three cases. The trends of the first-order and the total-effect index are very similar. Thus, the same conclusion can be drawn."}}]}, "properties": [], "parentId": "373", "childIds": [], "backendDOMNodeId": 8866}, {"nodeId": "1363", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 12", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 12"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "374", "childIds": ["2253"], "backendDOMNodeId": 8868, "browsergym_id": "761a3f5f-c161-4113"}, {"nodeId": "1364", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " shows the flow field of the flat plane. Since there are up to 225 cases in total, a reference case for the flow field example is defined with the following parameters: ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " shows the flow field of the flat plane. Since there are up to 225 cases in total, a reference case for the flow field example is defined with the following parameters: "}}]}, "properties": [], "parentId": "374", "childIds": [], "backendDOMNodeId": 8870}, {"nodeId": "1365", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "374", "childIds": ["2254"], "backendDOMNodeId": 8871, "browsergym_id": "c268a0e3-bd71-40b8"}, {"nodeId": "1366", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " = 14.0\u00a0mm, ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " = 14.0\u00a0mm, "}}]}, "properties": [], "parentId": "374", "childIds": [], "backendDOMNodeId": 8873}, {"nodeId": "1367", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "374", "childIds": ["2255"], "backendDOMNodeId": 8874, "browsergym_id": "8c345f40-88de-4a30"}, {"nodeId": "1368", "ignored": false, "role": {"type": "role", "value": "generic"}, "chromeRole": {"type": "internalRole", "value": 88}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "374", "childIds": ["2256", "2257"], "backendDOMNodeId": 8877, "browsergym_id": "960fa8d1-7ab4-4582"}, {"nodeId": "1369", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ", ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", "}}]}, "properties": [], "parentId": "374", "childIds": [], "backendDOMNodeId": 8908}, {"nodeId": "1370", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "374", "childIds": ["2258"], "backendDOMNodeId": 8909, "browsergym_id": "799d46b0-b6a7-4b1a"}, {"nodeId": "1371", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " = 1.2, ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " = 1.2, "}}]}, "properties": [], "parentId": "374", "childIds": [], "backendDOMNodeId": 8911}, {"nodeId": "1372", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "374", "childIds": ["2259"], "backendDOMNodeId": 8912, "browsergym_id": "d0df8c16-37d3-4336"}, {"nodeId": "1373", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " = 0.5. ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " = 0.5. "}}]}, "properties": [], "parentId": "374", "childIds": [], "backendDOMNodeId": 8914}, {"nodeId": "1374", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 12A", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 12A"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "374", "childIds": ["2260"], "backendDOMNodeId": 8915, "browsergym_id": "74ce2904-8f45-48a8"}, {"nodeId": "1375", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " is the top view. It can be found that the flow field is highly symmetric on the top surface, and the green region is the widest temperature region, which occupies more than half the length of the region downstream of the confluence on the centerline. Moreover, the lateral diffusion is not evident since the width of the coolant stream keeps nearly equal to the hole diameter. ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " is the top view. It can be found that the flow field is highly symmetric on the top surface, and the green region is the widest temperature region, which occupies more than half the length of the region downstream of the confluence on the centerline. Moreover, the lateral diffusion is not evident since the width of the coolant stream keeps nearly equal to the hole diameter. "}}]}, "properties": [], "parentId": "374", "childIds": [], "backendDOMNodeId": 8917}, {"nodeId": "1376", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 12B", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 12B"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "374", "childIds": ["2261"], "backendDOMNodeId": 8918, "browsergym_id": "cfdb64ca-091b-429a"}, {"nodeId": "1377", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " is the front view of the flow field. It is detectable that right downstream the coolant hole, a reverse vortex pair is generated that drives the coolant jet away from the blade. A portion of the coolant on the top blends into the mainstream. The flow field shows that as the two jets move forward, the convergence of the two streams becomes more pronounced. Thus it is true that the coolant jet performs well only at a limited distance downstream of the confluence point. The reference case has a blowing ratio of less than 1, which means that the mainstream moves faster than the coolant jet, so ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " is the front view of the flow field. It is detectable that right downstream the coolant hole, a reverse vortex pair is generated that drives the coolant jet away from the blade. A portion of the coolant on the top blends into the mainstream. The flow field shows that as the two jets move forward, the convergence of the two streams becomes more pronounced. Thus it is true that the coolant jet performs well only at a limited distance downstream of the confluence point. The reference case has a blowing ratio of less than 1, which means that the mainstream moves faster than the coolant jet, so "}}]}, "properties": [], "parentId": "374", "childIds": [], "backendDOMNodeId": 8920}, {"nodeId": "1378", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 12C", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 12C"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "374", "childIds": ["2262"], "backendDOMNodeId": 8921, "browsergym_id": "3f810e78-71fa-4f3e"}, {"nodeId": "1379", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " indicates in the cross-section view that the general effect of gas motion is moving from the coolant jet to the hot mainstream. This leads to the coolant jet\u2019s diffusion and thus significantly impairs the cooling effectiveness. While in the cross-section view, we can also find that the coolant jet, which stays near the surface of the turbine blade, is rotating in a closed loop, that ensures that coolant is not lifted away from the blade, and achieves better cooling effectiveness at the surface layer of the blades.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " indicates in the cross-section view that the general effect of gas motion is moving from the coolant jet to the hot mainstream. This leads to the coolant jet\u2019s diffusion and thus significantly impairs the cooling effectiveness. While in the cross-section view, we can also find that the coolant jet, which stays near the surface of the turbine blade, is rotating in a closed loop, that ensures that coolant is not lifted away from the blade, and achieves better cooling effectiveness at the surface layer of the blades."}}]}, "properties": [], "parentId": "374", "childIds": [], "backendDOMNodeId": 8923}, {"nodeId": "1380", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "FIGURE 12", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "FIGURE 12"}}]}, "properties": [], "parentId": "376", "childIds": [], "backendDOMNodeId": 8926}, {"nodeId": "1381", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "www.frontiersin.org", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "www.frontiersin.org"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "377", "childIds": ["2263"], "backendDOMNodeId": 8928, "browsergym_id": "d82c8067-c914-41b6"}, {"nodeId": "1382", "ignored": false, "role": {"type": "role", "value": "paragraph"}, "chromeRole": {"type": "internalRole", "value": 133}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "377", "childIds": ["2264", "2265", "2266", "2267", "2268", "2269", "2270", "2271"], "backendDOMNodeId": 8930, "browsergym_id": "c35b68ff-a064-4bee"}, {"nodeId": "1383", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "During the experiment and analysis, it is found that under the small blowing ratio case of ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "During the experiment and analysis, it is found that under the small blowing ratio case of "}}]}, "properties": [], "parentId": "380", "childIds": [], "backendDOMNodeId": 8946}, {"nodeId": "1384", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "380", "childIds": ["2272"], "backendDOMNodeId": 8947, "browsergym_id": "3b3aa754-b71d-4ec8"}, {"nodeId": "1385", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " = 0.5, the coolant hole diameter d has more impact sensitivity on the general film cooling effectiveness, compared with the coolant inclination angle. However, under a larger blowing ratio of 1.0, the coolant inclination angle has more effect than hole diameter. To further explain the flow physics that account for this result, the flow field of the cases under low and high blowing ratios, including ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " = 0.5, the coolant hole diameter d has more impact sensitivity on the general film cooling effectiveness, compared with the coolant inclination angle. However, under a larger blowing ratio of 1.0, the coolant inclination angle has more effect than hole diameter. To further explain the flow physics that account for this result, the flow field of the cases under low and high blowing ratios, including "}}]}, "properties": [], "parentId": "380", "childIds": [], "backendDOMNodeId": 8949}, {"nodeId": "1386", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "380", "childIds": ["2273"], "backendDOMNodeId": 8950, "browsergym_id": "c6b4a809-bf82-4bb1"}, {"nodeId": "1387", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " = 10.5\u00a0mm and 11.5\u00a0mm, coolant inclination angles of 20", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " = 10.5\u00a0mm and 11.5\u00a0mm, coolant inclination angles of 20"}}]}, "properties": [], "parentId": "380", "childIds": [], "backendDOMNodeId": 8952}, {"nodeId": "1388", "ignored": false, "role": {"type": "role", "value": "generic"}, "chromeRole": {"type": "internalRole", "value": 88}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "380", "childIds": ["2274", "2275"], "backendDOMNodeId": 8953, "browsergym_id": "afc4ae16-73e3-401b"}, {"nodeId": "1389", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " and 30", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " and 30"}}]}, "properties": [], "parentId": "380", "childIds": [], "backendDOMNodeId": 8973}, {"nodeId": "1390", "ignored": false, "role": {"type": "role", "value": "generic"}, "chromeRole": {"type": "internalRole", "value": 88}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "380", "childIds": ["2276", "2277"], "backendDOMNodeId": 8974, "browsergym_id": "482ab9b0-9e47-43d1"}, {"nodeId": "1391", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ", and in both x-z and y-z direction are compared and analyzed. From a top view, by comparing ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", and in both x-z and y-z direction are compared and analyzed. From a top view, by comparing "}}]}, "properties": [], "parentId": "380", "childIds": [], "backendDOMNodeId": 8994}, {"nodeId": "1392", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figures 13A,B", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figures 13A,B"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "380", "childIds": ["2278"], "backendDOMNodeId": 8995, "browsergym_id": "4204ed63-cd4d-4c7a"}, {"nodeId": "1393", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " and ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " and "}}]}, "properties": [], "parentId": "380", "childIds": [], "backendDOMNodeId": 8997}, {"nodeId": "1394", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figures 13A,C", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figures 13A,C"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "380", "childIds": ["2279"], "backendDOMNodeId": 8998, "browsergym_id": "ef25f3e6-6d5e-432f"}, {"nodeId": "1395", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ", we find that the low-temperature region at the center of the coolant hole expands to a larger degree under the influence of diameter change. This discovery implies that under a small blowing ratio of ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", we find that the low-temperature region at the center of the coolant hole expands to a larger degree under the influence of diameter change. This discovery implies that under a small blowing ratio of "}}]}, "properties": [], "parentId": "380", "childIds": [], "backendDOMNodeId": 9000}, {"nodeId": "1396", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "380", "childIds": ["2280"], "backendDOMNodeId": 9001, "browsergym_id": "9c354de5-0380-46b6"}, {"nodeId": "1397", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " = 0.5, the change in cooling effectiveness due to diameter change is larger than the change due to inclination angle. As for the case where the blowing ratio is as large as ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " = 0.5, the change in cooling effectiveness due to diameter change is larger than the change due to inclination angle. As for the case where the blowing ratio is as large as "}}]}, "properties": [], "parentId": "380", "childIds": [], "backendDOMNodeId": 9003}, {"nodeId": "1398", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "380", "childIds": ["2281"], "backendDOMNodeId": 9004, "browsergym_id": "f692b2fa-a498-4723"}, {"nodeId": "1399", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " = 1.0, ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " = 1.0, "}}]}, "properties": [], "parentId": "380", "childIds": [], "backendDOMNodeId": 9006}, {"nodeId": "1400", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figures 13D,E", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figures 13D,E"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "380", "childIds": ["2282"], "backendDOMNodeId": 9007, "browsergym_id": "382facdf-4af5-4b3e"}, {"nodeId": "1401", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " and ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " and "}}]}, "properties": [], "parentId": "380", "childIds": [], "backendDOMNodeId": 9009}, {"nodeId": "1402", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figures 13D,F", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figures 13D,F"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "380", "childIds": ["2283"], "backendDOMNodeId": 9010, "browsergym_id": "2f8807cd-9c42-4a1f"}, {"nodeId": "1403", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " shows that the influence of the inclination angle is larger than the influence of the diameter, because the coolant flow in (F) shrinks dramatically, while the ones in (D) and (E) are similar to each other. ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " shows that the influence of the inclination angle is larger than the influence of the diameter, because the coolant flow in (F) shrinks dramatically, while the ones in (D) and (E) are similar to each other. 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The four subplots study the three single-parameter effects and the combined effect.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " shows the probability distribution of general cooling effectiveness at different blowing ratios. The four subplots study the three single-parameter effects and the combined effect."}}]}, "properties": [], "parentId": "390", "childIds": [], "backendDOMNodeId": 9223}, {"nodeId": "1435", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "FIGURE 15", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "FIGURE 15"}}]}, "properties": [], "parentId": "392", "childIds": [], "backendDOMNodeId": 9226}, {"nodeId": "1436", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "www.frontiersin.org", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "www.frontiersin.org"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "393", "childIds": ["2402"], "backendDOMNodeId": 9228, "browsergym_id": "37d7fa33-d8c7-4191"}, {"nodeId": "1437", "ignored": false, "role": {"type": "role", "value": "paragraph"}, "chromeRole": {"type": "internalRole", "value": 133}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "393", "childIds": ["2403", "2404", "2405", "2406", "2407", "2408", "2409", "2410", "2411", "2412", "2413", "2414", "2415", "2416", "2417", "2418"], "backendDOMNodeId": 9230, "browsergym_id": "7d5f4714-2222-460c"}, {"nodeId": "1438", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "As shown in ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "As shown in "}}]}, "properties": [], "parentId": "396", "childIds": [], "backendDOMNodeId": 9258}, {"nodeId": "1439", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 15A", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 15A"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "396", "childIds": ["2419"], "backendDOMNodeId": 9259, "browsergym_id": "3e0dddd7-3662-4595"}, {"nodeId": "1440", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ", the PDF distribution of the coolant hole diameter is studied. When the blowing ratio is 0.5, the 95% confidence interval due to hole diameter is [0.070, 0.113]. However, those for blowing ratios of 1.0 and 1.5 are [0.030, 0.049] and [0.014, 0.017], respectively. The corresponding interval length for the three blowing ratios are 0.043, 0.019, and 0.003, respectively. The result shows that as ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", the PDF distribution of the coolant hole diameter is studied. When the blowing ratio is 0.5, the 95% confidence interval due to hole diameter is [0.070, 0.113]. However, those for blowing ratios of 1.0 and 1.5 are [0.030, 0.049] and [0.014, 0.017], respectively. The corresponding interval length for the three blowing ratios are 0.043, 0.019, and 0.003, respectively. The result shows that as "}}]}, "properties": [], "parentId": "396", "childIds": [], "backendDOMNodeId": 9261}, {"nodeId": "1441", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "396", "childIds": ["2420"], "backendDOMNodeId": 9262, "browsergym_id": "054993c6-9fff-4768"}, {"nodeId": "1442", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " is increasing, the 95% confidence interval due to hole diameter narrows rapidly, almost halving each time, and the mean of general cooling effectiveness decreases continuously, indicating that the uncertainty caused by hole diameter decreases.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " is increasing, the 95% confidence interval due to hole diameter narrows rapidly, almost halving each time, and the mean of general cooling effectiveness decreases continuously, indicating that the uncertainty caused by hole diameter decreases."}}]}, "properties": [], "parentId": "396", "childIds": [], "backendDOMNodeId": 9264}, {"nodeId": "1443", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "For the hole inclination angle, as shown in ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "For the hole inclination angle, as shown in "}}]}, "properties": [], "parentId": "397", "childIds": [], "backendDOMNodeId": 9266}, {"nodeId": "1444", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 15B", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 15B"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "397", "childIds": ["2421"], "backendDOMNodeId": 9267, "browsergym_id": "8fe4bf06-6a58-4459"}, {"nodeId": "1445", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ", when the ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", when the "}}]}, "properties": [], "parentId": "397", "childIds": [], "backendDOMNodeId": 9269}, {"nodeId": "1446", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "397", "childIds": ["2422"], "backendDOMNodeId": 9270, "browsergym_id": "5aaa524f-0024-4065"}, {"nodeId": "1447", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " increases, the uncertainty effect maintains a high level due to the hole inclination angle. The confidence intervals remain wide for all low, medium, and high blowing ratios. This is different from the case for hole diameter. With the increase of ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " increases, the uncertainty effect maintains a high level due to the hole inclination angle. The confidence intervals remain wide for all low, medium, and high blowing ratios. This is different from the case for hole diameter. With the increase of "}}]}, "properties": [], "parentId": "397", "childIds": [], "backendDOMNodeId": 9272}, {"nodeId": "1448", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "397", "childIds": ["2423"], "backendDOMNodeId": 9273, "browsergym_id": "d5462086-3d51-44aa"}, {"nodeId": "1449", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ", the range of variation of general film cooling effectiveness of inclination angle decreases from 0.030, 0.029 to 0.023 after simple calculation. It can be concluded that with the increasing of the blowing ratio, the uncertainty caused by the inclination angle ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", the range of variation of general film cooling effectiveness of inclination angle decreases from 0.030, 0.029 to 0.023 after simple calculation. It can be concluded that with the increasing of the blowing ratio, the uncertainty caused by the inclination angle "}}]}, "properties": [], "parentId": "397", "childIds": [], "backendDOMNodeId": 9275}, {"nodeId": "1450", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "397", "childIds": ["2424"], "backendDOMNodeId": 9276, "browsergym_id": "ce7b4b42-2ad5-46ca"}, {"nodeId": "1451", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " reduces, but with a lower decreasing speed than the hole diameter.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " reduces, but with a lower decreasing speed than the hole diameter."}}]}, "properties": [], "parentId": "397", "childIds": [], "backendDOMNodeId": 9278}, {"nodeId": "1452", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 15C", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 15C"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "398", "childIds": ["2425"], "backendDOMNodeId": 9280, "browsergym_id": "eff70d50-5e18-44b1"}, {"nodeId": "1453", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " shows that the magnitude of the length of the confidence interval of the density ratio is the smallest among all parameters. However, the ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " shows that the magnitude of the length of the confidence interval of the density ratio is the smallest among all parameters. However, the "}}]}, "properties": [], "parentId": "398", "childIds": [], "backendDOMNodeId": 9282}, {"nodeId": "1454", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "398", "childIds": ["2426"], "backendDOMNodeId": 9283, "browsergym_id": "320c200a-75d1-414b"}, {"nodeId": "1455", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " value of the density ratio is the highest, the minimum value of which still exceeds 160 in the case of the ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " value of the density ratio is the highest, the minimum value of which still exceeds 160 in the case of the "}}]}, "properties": [], "parentId": "398", "childIds": [], "backendDOMNodeId": 9285}, {"nodeId": "1456", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "398", "childIds": ["2427"], "backendDOMNodeId": 9286, "browsergym_id": "6fb54197-f65b-42f9"}, {"nodeId": "1457", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " = 1.0.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " = 1.0."}}]}, "properties": [], "parentId": "398", "childIds": [], "backendDOMNodeId": 9288}, {"nodeId": "1458", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "The uncertainty of the combined effect decreases as ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "The uncertainty of the combined effect decreases as "}}]}, "properties": [], "parentId": "399", "childIds": [], "backendDOMNodeId": 9290}, {"nodeId": "1459", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "399", "childIds": ["2428"], "backendDOMNodeId": 9291, "browsergym_id": "14ff54c7-1e45-45db"}, {"nodeId": "1460", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " rises, and the combined effect is more prominent than all three single effects. In ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " rises, and the combined effect is more prominent than all three single effects. In "}}]}, "properties": [], "parentId": "399", "childIds": [], "backendDOMNodeId": 9293}, {"nodeId": "1461", "ignored": false, "role": {"type": "role", "value": "link"}, "chromeRole": {"type": "internalRole", "value": 110}, "name": {"type": "computedString", "value": "Figure 15D", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "contents", "value": {"type": "computedString", "value": "Figure 15D"}}, {"type": "attribute", "attribute": "title", "superseded": true}]}, "properties": [{"name": "focusable", "value": {"type": "booleanOrUndefined", "value": true}}], "parentId": "399", "childIds": ["2429"], "backendDOMNodeId": 9294, "browsergym_id": "86bc56eb-77da-43d8"}, {"nodeId": "1462", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ", for example, the 95% confidence intervals are [0.062, 0.112], [0.023, 0.058], [0.004, 0.027], and the interval lengths are 0.060, 0.035, and 0.023, respectively. Compared with the single effect caused by the inclination angle ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", for example, the 95% confidence intervals are [0.062, 0.112], [0.023, 0.058], [0.004, 0.027], and the interval lengths are 0.060, 0.035, and 0.023, respectively. Compared with the single effect caused by the inclination angle "}}]}, "properties": [], "parentId": "399", "childIds": [], "backendDOMNodeId": 9296}, {"nodeId": "1463", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "399", "childIds": ["2430"], "backendDOMNodeId": 9297, "browsergym_id": "36f9b327-71f3-40e2"}, {"nodeId": "1464", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": ", the interval length of the combination becomes wider.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": ", the interval length of the combination becomes wider."}}]}, "properties": [], "parentId": "399", "childIds": [], "backendDOMNodeId": 9299}, {"nodeId": "1465", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "Conclusion", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "Conclusion"}}]}, "properties": [], "parentId": "401", "childIds": [], "backendDOMNodeId": 9302}, {"nodeId": "1466", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "This study aims to improve the gas turbine performance by strengthening the film cooling effectiveness, especially by focusing on the uncertainty of the three significant parameters, including single hole diameter, density ratio, and inclination angle, on the film cooling effectiveness under low, medium, and high blowing ratios. The uncertainty analysis was conducted using a deep-learning-based ANN model and uncertainty quantification method. Firstly, all related indices and research regions are defined at the beginning. Due to its best performance, the six-million grid size and the RNG k-\u03b5 model are chosen for the turbulence model. Secondly, a high-performance ANN model is delicately constructed for training and to seek the non-linear correlation between the parameter input and the cooling effectiveness output. CFD provides training and validation datasets. Finally, the sensitivity of three parameters is quantified, and uncertainty quantification is conducted to quantify the single and combined effect of the uncertainty of these three parameters on the general cooling effectiveness. The following conclusions are drawn.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "This study aims to improve the gas turbine performance by strengthening the film cooling effectiveness, especially by focusing on the uncertainty of the three significant parameters, including single hole diameter, density ratio, and inclination angle, on the film cooling effectiveness under low, medium, and high blowing ratios. The uncertainty analysis was conducted using a deep-learning-based ANN model and uncertainty quantification method. Firstly, all related indices and research regions are defined at the beginning. Due to its best performance, the six-million grid size and the RNG k-\u03b5 model are chosen for the turbulence model. Secondly, a high-performance ANN model is delicately constructed for training and to seek the non-linear correlation between the parameter input and the cooling effectiveness output. CFD provides training and validation datasets. Finally, the sensitivity of three parameters is quantified, and uncertainty quantification is conducted to quantify the single and combined effect of the uncertainty of these three parameters on the general cooling effectiveness. The following conclusions are drawn."}}]}, "properties": [], "parentId": "402", "childIds": [], "backendDOMNodeId": 9304}, {"nodeId": "1467", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "1. After careful hyperparameter selection and training, the ANN model built in this study shows excellent performance in predicting the general and fixed-cord-averaged film cooling effectiveness according to input parameters compared with the data simulated by the CFD method. The QE value for fixed-cord-averaged film cooling effectiveness in training and validation datasets are 0.29% and 0.32%. The QE value for general film cooling effectiveness in training and validation datasets are 0.35% and 0.30%.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "1. After careful hyperparameter selection and training, the ANN model built in this study shows excellent performance in predicting the general and fixed-cord-averaged film cooling effectiveness according to input parameters compared with the data simulated by the CFD method. The QE value for fixed-cord-averaged film cooling effectiveness in training and validation datasets are 0.29% and 0.32%. The QE value for general film cooling effectiveness in training and validation datasets are 0.35% and 0.30%."}}]}, "properties": [], "parentId": "403", "childIds": [], "backendDOMNodeId": 9306}, {"nodeId": "1468", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "2. The Sobol method based on MC simulation shows that at a small blowing ratio, the coolant tube\u2019s diameter and inclination angle are two main factors to the cooling effectiveness, and the former has a more dominant effect. At medium and large blowing ratios, the inclination angle is the only leading factor to the film cooling effectiveness. Furthermore, the maximum effect of the inclination angle increases as the blowing ratio grows.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "2. The Sobol method based on MC simulation shows that at a small blowing ratio, the coolant tube\u2019s diameter and inclination angle are two main factors to the cooling effectiveness, and the former has a more dominant effect. At medium and large blowing ratios, the inclination angle is the only leading factor to the film cooling effectiveness. Furthermore, the maximum effect of the inclination angle increases as the blowing ratio grows."}}]}, "properties": [], "parentId": "404", "childIds": [], "backendDOMNodeId": 9308}, {"nodeId": "1469", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "3. Uncertainty quantification reveals that the uncertainty of hole diameter, inclination angle, and density ratio all decrease as the blowing ratio rises. Moreover, the combined effect shows a higher impact on the general cooling effectiveness than any single effect. Within three parameters, the variation of the uncertainty interval of the hole diameter at three blowing ratios is the most obvious. Furthermore, the inclination angle ", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "3. Uncertainty quantification reveals that the uncertainty of hole diameter, inclination angle, and density ratio all decrease as the blowing ratio rises. Moreover, the combined effect shows a higher impact on the general cooling effectiveness than any single effect. Within three parameters, the variation of the uncertainty interval of the hole diameter at three blowing ratios is the most obvious. Furthermore, the inclination angle "}}]}, "properties": [], "parentId": "405", "childIds": [], "backendDOMNodeId": 9310}, {"nodeId": "1470", "ignored": false, "role": {"type": "role", "value": "emphasis"}, "chromeRole": {"type": "internalRole", "value": 81}, "name": {"type": "computedString", "value": "", "sources": [{"type": "relatedElement", "attribute": "aria-labelledby"}, {"type": "attribute", "attribute": "aria-label"}, {"type": "attribute", "attribute": "title"}]}, "properties": [], "parentId": "405", "childIds": ["2431"], "backendDOMNodeId": 9311, "browsergym_id": "c0209683-0b0f-4efc"}, {"nodeId": "1471", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": " has the most extensive uncertain influence on the general film cooling effectiveness among the three single parameters", "sources": [{"type": "contents", "value": {"type": "computedString", "value": " has the most extensive uncertain influence on the general film cooling effectiveness among the three single parameters"}}]}, "properties": [], "parentId": "405", "childIds": [], "backendDOMNodeId": 9313}, {"nodeId": "1472", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "Data Availability Statement", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "Data Availability Statement"}}]}, "properties": [], "parentId": "407", "childIds": [], "backendDOMNodeId": 9316}, {"nodeId": "1473", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "The data that support the findings of this study are available from the corresponding author upon reasonable request.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "The data that support the findings of this study are available from the corresponding author upon reasonable request."}}]}, "properties": [], "parentId": "408", "childIds": [], "backendDOMNodeId": 9318}, {"nodeId": "1474", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "Author Contributions", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "Author Contributions"}}]}, "properties": [], "parentId": "410", "childIds": [], "backendDOMNodeId": 9321}, {"nodeId": "1475", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "YW: Conceptualization, data curation, formal analysis, investigation, methodology, resources, software, validation, and writing\u2013original draft. XQ: Data curation, formal analysis, investigation, resources, visualization, and writing\u2014original draft. SQ: Investigation, resources, visualization, and writing\u2014original draft. YS: Data curation, formal analysis, methodology, visualization, and writing\u2014original draft. WW: Resources, software, and validation. JC: Conceptualization, formal analysis, funding acquisition, investigation, project administration, software, supervision, visualization, writing\u2014review and editing.", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "YW: Conceptualization, data curation, formal analysis, investigation, methodology, resources, software, validation, and writing\u2013original draft. XQ: Data curation, formal analysis, investigation, resources, visualization, and writing\u2014original draft. SQ: Investigation, resources, visualization, and writing\u2014original draft. 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JC: Conceptualization, formal analysis, funding acquisition, investigation, project administration, software, supervision, visualization, writing\u2014review and editing."}}]}, "properties": [], "parentId": "411", "childIds": [], "backendDOMNodeId": 9323}, {"nodeId": "1476", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "Funding", "sources": [{"type": "contents", "value": {"type": "computedString", "value": "Funding"}}]}, "properties": [], "parentId": "413", "childIds": [], "backendDOMNodeId": 9326}, {"nodeId": "1477", "ignored": false, "role": {"type": "internalRole", "value": "StaticText"}, "chromeRole": {"type": "internalRole", "value": 158}, "name": {"type": "computedString", "value": "This study was supported in part by State Key Laboratory for Aerodynamics, the Zhejiang University/University of Illinois at Urbana-Champaign Institute and National Natural Science Foundation of China (Grant No. 52106060 and 92152202). 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