Efficient genetic algorithm based robust design method for compressor fan blades

被引:0
|
作者
Kumar, Apurva [1 ]
Keane, A. J. [1 ]
Nair, P. B. [1 ]
Shahpar, S. [1 ]
机构
[1] Univ Southampton, Sch Engn Sci, Computat Engn & Design Grp, Southampton SO17 1BJ, Hants, England
关键词
D O I
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中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper presents an efficient genetic algorithm based methodology for robust design that produces compressor fan blades tolerant against erosion. A novel geometry modeling method is employed to create eroded compressor fan blade sections. A multigrid Reynolds-Averaged Navier Stokes (RANS) solver HYDRA with Spalart Allmaras turbulence model is used for CFD simulations to calculate the pressure losses. This is used in conjunction with Design of Experiment techniques to create Gaussian stochastic process surrogate models to predict the mean and variance of the performance. The Non-dominated Sorting Genetic Algorithm (NSGA-II) is employed for the multi-objective optimization to find the global Pareto-optimal front. This enables the designer to trade off between mean and variance of performance to propose robust designs.
引用
收藏
页码:1205 / 1213
页数:9
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