储能科学与技术2025，Vol.14Issue(4)：1522-1532,11.DOI:10.19799/j.cnki.2095-4239.2024.1011
压缩空气储能轴流压缩机叶片应力优化方法
Research on blade stress optimization method of axial flow compressor in compressed air energy storage system
摘要
Abstract
Compressed air energy storage(CAES)systems are recognized as one of the most promising large-scale physical energy storage technologies.At the heart of these systems lies the axial flow compressor,whose safety and operational stability are critical for ensuring the economic viability and safe use of advanced CAES.Within the compressor,the blades play a key role in energy conversion but are vulnerable to fatigue damage during operation.The stacking line of the blade can effectively adjust the stress distribution characteristics.This study focuses on the structural optimization of a 1.5-stage axial flow compressor within a CAES system.Latin hypercube planning(LHS)is employed for parameter selection,a radial basis function neural network(RBFNN)is used to establish the agent model,and the non-dominated sorting genetic algorithm-Ⅱ(NSGA-Ⅱ)is applied to capture the target value.Together,these approaches establish an integrated parametric optimization framework for three-dimensional bending and sweeping structure modeling of axial flow blades.The optimization results show that the maximum equivalent stress of the optimized blade decreases from 376.8 MPa to 255.9 MPa,achieving a stress reduction of 32.1%.The blade stress distribution is primarily influenced by centrifugal forces,while appropriate bending and sweeping modifications can effectively adjust the center of gravity and the centrifugal bending moment for each blade section.Notably,the optimization method does not significantly impact the flow field distribution,rotor surface load distribution,and tip clearance energy dissipation and achieve the decoupling of aerodynamic performance and structural stress distribution.关键词
轴流压缩机/积叠方式/参数化建模/数值模拟Key words
axial compressor/stacking method/parametric modeling/numerical simulation分类
能源与动力引用本文复制引用
石贵月,陶海亮,左志涛,李靖鑫,陈吉祥,陈家希,陈海生..压缩空气储能轴流压缩机叶片应力优化方法[J].储能科学与技术,2025,14(4):1522-1532,11.基金项目
国家重点研发计划(2023YFB2406500),国家自然科学基金(52306285),山东能源研究院企业联合基金项目(U202301). （2023YFB2406500）
