基于源项法的气膜冷却涡轮叶片多目标优化

Multi-Objective Optimization of Film-Cooled Turbine with Source Term Method

关键词:  涡轮  气膜冷却  数值模拟  源项法  多目标优化 

Key words:  Turbine  Film cooling  Numerical simulation  Source term method  Multi-objective optimization

摘要:

以GE-E³高压涡轮第一级气冷导叶为研究对象,通过多目标遗传算法优化气膜孔布局以降低叶片表面温度。其中采用源项法模拟全场气膜冷却效果,该方法节省计算量的同时无需对气膜孔划分网格,通过对比实验结果后认为,源项法可以较好地模拟出冷气覆盖效果如表面动量损失等。在此基础上采用多目标遗传算法NSGA-II (Nondominated Sorting Genetic Algorithm II),以气膜孔的出气角及流向位置为设计变量,以叶片表面最高温度及平均温度为优化目标。结果表明叶片表面温度分布有所改善,其中压力面优化效果要好于吸力面。 

Abstract:

A multi-objective genetic algorithm optimization procedure was demonstrated on the film cooled stator of the first high pressure stage of GE-E^3to decrease the temperature on the blade. Firstly, source term method was employed to simulate the effect of overall film cooling, considering it was cheap in term of CPU consumption and did not require any mesh adaption in the presence of cooling holes. The loss of momentum near the wall caused by the injected coolant could be observed from the simulated results, which agreed well with the experimental results. Secondly, multi-objective optimization method NSGA-II (Nondominated Sorting Genetic Algorithm II) was used to minimize the maximum temperature and average temperature of the blade. The inject angles and streamwise positions were varied in the design space. The results demonstrate that the temperature distribution on the blade has been improved, and the pressure side has better cooling effect compared with suction side. 