一种核主泵水力模型高效低轴向载荷优化改型策略

An Optimization Strategy for High Efficiency and Low Axial Load Design of Hydraulic Model for Nuclear Reactor Coolant Pump

针对当前多数研究中仅改善反应堆冷却剂泵(核主泵)性能特性而缺乏考虑载荷特性的不足,在一种新的叶轮轴面流道设计方法基础上,联合应用径向基神经网络和多目标遗传算法,构建了以高性能、低轴向载荷为目标的优化策略。为了验证优化策略的可行性,以前期设计的核主泵缩尺模型为对象迚行了改型设计。结果表明:新的优化策略仅需要3个变量控制、15组采样数据,便可成功实现对核主泵的优化改型;优化结果在设计工冴点效率较目标叶轮提高了0.9%,扬程提高了0.6 m,轴向载荷降低了约200 N;代理模型预测结果定量证明优化设计中扬程的增加容易引发轴向载荷的提升。

Aiming at the single consideration of the performance characteristics while the lack of the load characteristics in most studies about the reactor coolant pump(the main pump),a new impeller meridian design approach along with the radial basis function neural network and the multi-optimization algorithm was herein adopted,as a result,a new optimization strategy whose targets were the higher performance and the lower axial load was established.To verify the effectiveness of the proposed optimization strategy,it was then applied into the practical design process whose design target was the previous scaled main pump.It could be found as follows:with only three control variables and fifteen samples,the new strategy succeeded in optimizing the pump;in relative to the target pump,the efficiency of the optimal structure is increased by 0.9%,the head is increased by 0.6 m,while the axial load is decreased by about 200 N;the predicting results from the approximate model could quantitatively prove that the increasing of the head can easily lead to the increasing of the axial load.