Shubham Agarwal, L. Gicquel, F. Duchaine, N. Odier, J. Dombard, D. Bonneau, Michel Slusarz
{"title":"冷却孔形状优化的自主大涡模拟装置","authors":"Shubham Agarwal, L. Gicquel, F. Duchaine, N. Odier, J. Dombard, D. Bonneau, Michel Slusarz","doi":"10.1115/gt2021-59196","DOIUrl":null,"url":null,"abstract":"\n Film cooling is a common technique to manage turbine blade thermal environment. The geometry of the holes which are used to generate the cooling film is known to play a very important role on thermal performances and finding the most optimized shape involves rigorous experimental as well as numerical investigations to probe the many parameters at play. For the current study an automatic optimization tool is developed and then probed with the capability of performing hole shape optimization based on Large Eddy Simulation (LES) predictions. To do so, the particular geometry called shaped cooling hole is chosen as a baseline geometry for this optimization process. Relying on the response surface evaluation based on a reduced model approach, the use of a Design of Experiments (DOE) method allows probing a discrete set of values from the parameter space used to define the present shaped cooling hole. At first only two parameters are chosen out of the seven parameters defining the hole shape. This is followed by the automatic generation of the hole geometry, the corresponding computational domain and the associated meshes. Once the geometries and meshes are created, the numerical setup is autonomously completed for each of the cases including a first guess of the flow field to increase convergence of the simulation towards an exploitable solution. To finish, the LES fluid flow prediction is used to evaluate the discrete value of the problem response function which can then participate in the reduced model construction from which the optimization is derived.","PeriodicalId":204099,"journal":{"name":"Volume 5A: Heat Transfer — Combustors; Film Cooling","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-06-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Autonomous Large Eddy Simulations Setup for Cooling Hole Shape Optimization\",\"authors\":\"Shubham Agarwal, L. Gicquel, F. Duchaine, N. Odier, J. Dombard, D. Bonneau, Michel Slusarz\",\"doi\":\"10.1115/gt2021-59196\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"\\n Film cooling is a common technique to manage turbine blade thermal environment. The geometry of the holes which are used to generate the cooling film is known to play a very important role on thermal performances and finding the most optimized shape involves rigorous experimental as well as numerical investigations to probe the many parameters at play. For the current study an automatic optimization tool is developed and then probed with the capability of performing hole shape optimization based on Large Eddy Simulation (LES) predictions. To do so, the particular geometry called shaped cooling hole is chosen as a baseline geometry for this optimization process. Relying on the response surface evaluation based on a reduced model approach, the use of a Design of Experiments (DOE) method allows probing a discrete set of values from the parameter space used to define the present shaped cooling hole. At first only two parameters are chosen out of the seven parameters defining the hole shape. This is followed by the automatic generation of the hole geometry, the corresponding computational domain and the associated meshes. Once the geometries and meshes are created, the numerical setup is autonomously completed for each of the cases including a first guess of the flow field to increase convergence of the simulation towards an exploitable solution. To finish, the LES fluid flow prediction is used to evaluate the discrete value of the problem response function which can then participate in the reduced model construction from which the optimization is derived.\",\"PeriodicalId\":204099,\"journal\":{\"name\":\"Volume 5A: Heat Transfer — Combustors; Film Cooling\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-06-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Volume 5A: Heat Transfer — Combustors; Film Cooling\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1115/gt2021-59196\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Volume 5A: Heat Transfer — Combustors; Film Cooling","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1115/gt2021-59196","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Autonomous Large Eddy Simulations Setup for Cooling Hole Shape Optimization
Film cooling is a common technique to manage turbine blade thermal environment. The geometry of the holes which are used to generate the cooling film is known to play a very important role on thermal performances and finding the most optimized shape involves rigorous experimental as well as numerical investigations to probe the many parameters at play. For the current study an automatic optimization tool is developed and then probed with the capability of performing hole shape optimization based on Large Eddy Simulation (LES) predictions. To do so, the particular geometry called shaped cooling hole is chosen as a baseline geometry for this optimization process. Relying on the response surface evaluation based on a reduced model approach, the use of a Design of Experiments (DOE) method allows probing a discrete set of values from the parameter space used to define the present shaped cooling hole. At first only two parameters are chosen out of the seven parameters defining the hole shape. This is followed by the automatic generation of the hole geometry, the corresponding computational domain and the associated meshes. Once the geometries and meshes are created, the numerical setup is autonomously completed for each of the cases including a first guess of the flow field to increase convergence of the simulation towards an exploitable solution. To finish, the LES fluid flow prediction is used to evaluate the discrete value of the problem response function which can then participate in the reduced model construction from which the optimization is derived.