{"title":"一种有效的气动外形优化方法","authors":"S. Hazra","doi":"10.2514/6.2004-4628","DOIUrl":null,"url":null,"abstract":"We present simultaneous pseudo-timestepping as an efficient method for aerodynamic shape optimization. In this method, instead of solving the necessary optimality conditions by iterative techniques, pseudo-time embedded nonstationary system is integrated in time until a steady state is reached. The main advantages of this method are that it requires no additional globalization techniques and that a preconditioner can be used for convergence acceleration which stems from the reduced SQP method. The important issue of this method is the trade-off between the accuracy of the forward and adjoint solver and its impact on the computational cost to approach an optimum solution is addressed. The method is applied to a test case of drag reduction for an RAE2822 airfoil, keeping it’s thickness constant. The optimum overall cost of computation that is achieved in this method is less than 4 times that of the forward simulation run. Nomenclature (x, y) ∈ R :cartesian coordinates H :total enthalpy (ξ, η) ∈ [0, 1] :generalized coordinates M :Mach number Ω :flow field domain )∞ :values at free stream ∂Ω :flow field boundary γ :ratio of specific heats ~n := ( nx ny ) :unit outward normal Cref :chord length α :angle of attack CD :drag coefficient ρ :density I :cost unction u :x-component of velocity w :vector of state variables v :y-component of velocity q :vector of design variables p :pressure λ :vector of adjoint variables E :total energy J :Jacobian Cp :pressure coefficient B :reduced Hessian","PeriodicalId":142744,"journal":{"name":"Universität Trier, Mathematik/Informatik, Forschungsbericht","volume":"12 8 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2004-08-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"26","resultStr":"{\"title\":\"An Efficient Method for Aerodynamic Shape Optimization\",\"authors\":\"S. Hazra\",\"doi\":\"10.2514/6.2004-4628\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We present simultaneous pseudo-timestepping as an efficient method for aerodynamic shape optimization. In this method, instead of solving the necessary optimality conditions by iterative techniques, pseudo-time embedded nonstationary system is integrated in time until a steady state is reached. The main advantages of this method are that it requires no additional globalization techniques and that a preconditioner can be used for convergence acceleration which stems from the reduced SQP method. The important issue of this method is the trade-off between the accuracy of the forward and adjoint solver and its impact on the computational cost to approach an optimum solution is addressed. The method is applied to a test case of drag reduction for an RAE2822 airfoil, keeping it’s thickness constant. The optimum overall cost of computation that is achieved in this method is less than 4 times that of the forward simulation run. Nomenclature (x, y) ∈ R :cartesian coordinates H :total enthalpy (ξ, η) ∈ [0, 1] :generalized coordinates M :Mach number Ω :flow field domain )∞ :values at free stream ∂Ω :flow field boundary γ :ratio of specific heats ~n := ( nx ny ) :unit outward normal Cref :chord length α :angle of attack CD :drag coefficient ρ :density I :cost unction u :x-component of velocity w :vector of state variables v :y-component of velocity q :vector of design variables p :pressure λ :vector of adjoint variables E :total energy J :Jacobian Cp :pressure coefficient B :reduced Hessian\",\"PeriodicalId\":142744,\"journal\":{\"name\":\"Universität Trier, Mathematik/Informatik, Forschungsbericht\",\"volume\":\"12 8 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2004-08-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"26\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Universität Trier, Mathematik/Informatik, Forschungsbericht\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2514/6.2004-4628\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Universität Trier, Mathematik/Informatik, Forschungsbericht","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2514/6.2004-4628","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
An Efficient Method for Aerodynamic Shape Optimization
We present simultaneous pseudo-timestepping as an efficient method for aerodynamic shape optimization. In this method, instead of solving the necessary optimality conditions by iterative techniques, pseudo-time embedded nonstationary system is integrated in time until a steady state is reached. The main advantages of this method are that it requires no additional globalization techniques and that a preconditioner can be used for convergence acceleration which stems from the reduced SQP method. The important issue of this method is the trade-off between the accuracy of the forward and adjoint solver and its impact on the computational cost to approach an optimum solution is addressed. The method is applied to a test case of drag reduction for an RAE2822 airfoil, keeping it’s thickness constant. The optimum overall cost of computation that is achieved in this method is less than 4 times that of the forward simulation run. Nomenclature (x, y) ∈ R :cartesian coordinates H :total enthalpy (ξ, η) ∈ [0, 1] :generalized coordinates M :Mach number Ω :flow field domain )∞ :values at free stream ∂Ω :flow field boundary γ :ratio of specific heats ~n := ( nx ny ) :unit outward normal Cref :chord length α :angle of attack CD :drag coefficient ρ :density I :cost unction u :x-component of velocity w :vector of state variables v :y-component of velocity q :vector of design variables p :pressure λ :vector of adjoint variables E :total energy J :Jacobian Cp :pressure coefficient B :reduced Hessian