论文部分内容阅读
针对重型燃气轮机压气机雷诺数高而导致的转捩位置前移,开发了一种比可控扩散叶型(CDA)损失更小、工作范围更宽的前转捩叶型.采用正问题优化设计方法,将叶型几何参数化、叶片到叶片流场分析与遗传算法相结合,实现了叶型的自动优化.优化目标综合权衡了叶型损失和攻角范围,为减少优化变量的数目,应用了一种特别的叶型几何模型,将厚度分布与中弧线之间进行了一定的关联.优化得到的前转捩叶型的主要特征是吸力面速度峰值的位置前移至距前缘约10%弦长处,叶型中后部的速度变化更为平缓.最后根据优化结果总结了前转捩叶型的设计规律.
In order to advance the transfer position caused by the high Reynolds number of heavy-duty gas turbine compressor, a forward-swirling vane with a smaller loss than CDA and a wider working range was developed. Method, the geometric parameterization of the leaf blade, blade-to-blade flow field analysis and genetic algorithm combined to achieve the automatic optimization of leaf type.Optimization of the target comprehensive trade-off between leaf loss and angle of attack, in order to reduce the number of optimization variables, the application A special leaf geometry model is proposed to correlate the thickness distribution with the camber line.The main feature of the optimized shroud leaf type is that the peak position of the suction surface moves forward to about At the 10% chord length, the velocity in the back part of the leaf pattern changes more smoothly. Finally, the design rules of the pre-harvest leaf-leaf type are summarized based on the optimization results.