Using Whole Annealing Genetic Algorithms for the Turbine Cascade Inverse Design Problem  

作　　者：Jun Li Zhenping Feng Hidetoshi Nishida Nobuyuki Satofuka 

出　　处：《Journal of Thermal Science》1999年第1期32-37,共6页热科学学报（英文版）

摘　　要：Turbine cascade optimum design, the typical non-convex optimal problem, has long been a design challenge in the engineering fields. The new type hybrid Genetic Algorithms-whole annealing GeneticAlgorithms have been developed in this paper. Simulated annealing selection and non-uniform mutation are adopted in the whole annealing Genetic Algorithms. Whole annealing Genetic Algorithmsoptimal performance have been tested through mathematical test functions. On this basis, turbinecascade inverse design using whole annealing Genetic Algorithms have been presented. The B-Splinefunction is applied to represent the cascade shape. C-type grid and Godunov scheme are adopted toanalysis the cascade aerodynamic performance. The optimal problem aims to obtain an cascade shapefrom different initial cascade through the given target pressure distribution. The optimum cascadeshape is in well agreement with the target cascade shape. The numerical results show that the wholeannealing Genetic Algorithms are the powerful optimum tools for turbine optimum design or othercomplex engineering design problems.

关 键 词：genetic algorithms simulate annealing TURBINE CASCADE inverse design. 

分 类 号：TK14[动力工程及工程热物理—热能工程]