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SHU Xinwei
GU Chuangang
WANG Tong
YANG Bo
School of Mechanical Engineering,
Shanghai Jiaotong University,
Shanghai 200030, China |
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AERODYNAMIC OPTIMIZATION FOR TURBINE
BLADE BASED ON HIERARCHICAL FAIR COMPETITION GENETIC ALGORITHMS
WITH DYNAMIC NICHE*
Abstract:
A global optimization approach to turbine blade design based on hierarchical fair competition genetic algorithms with dynamic niche (HFCDN-GAs) coupled with Reynolds-averaged Navier-Stokes (RANS) equation is presented. In order to meet the search theory of GAs and the aerodynamic performances of turbine, Bezier curve is adopted to parameterize the turbine blade profile, and a fitness function pertaining to optimization is designed. The design variables are the control points’ ordinates of characteristic polygon of Bezier curve representing the turbine blade profile. The object function is the maximum lift-drag ratio of the turbine blade. The constraint conditions take into account the leading and trailing edge metal angle, and the strength and aerodynamic performances of turbine blade. And the treatment method of the constraint conditions is the flexible penalty function. The convergence history of test function indicates that HFCDN-GAs can locate the global optimum within a few search steps and have high robustness. The lift-drag ratio of the optimized blade is 8.3% higher than that of the original one. The results show that the proposed global optimization approach is effective for turbine blade.
Key words:
Turbine blade Reynolds-averaged Navier-stokes(RANS) equation Lift-drag ratio Optimum design |