Journal of Propulsion Technology ›› 2014, Vol. 35 ›› Issue (3): 328-334.

• Ship Propulsion • Previous Articles     Next Articles

Optimization of Multi-Stage Axial-Flow Compressor Based on Stochastic Ranking Differential Evolution Algorithm

  

  1. School of Power and Energy, Northwestern Polytechnical University, Xi’an 710072, China;School of Power and Energy, Northwestern Polytechnical University, Xi’an 710072, China
  • Published:2021-08-15

基于随机排序微分进化算法的多级轴流压气机优化技术

杨小东,刘 波   

  1. 西北工业大学 动力与能源学院, 陕西 西安 710072;西北工业大学 动力与能源学院, 陕西 西安 710072
  • 作者简介:杨小东(1986—),男,博士生,研究领域为叶轮机参数化设计及优化技术。 E-mail:yangxiaodong1986@163.com
  • 基金资助:
    国家自然科学基金资助项目 (51236006)。

Abstract: Stochastic Ranking Based Differential Algorithm is presented with the purpose of disposing constraints precisely and enhancing the reliability of the optimization of multi-stage axial compressor. Stochastic ranking is introduced to handle the complex constraints which are common emergence and then it is coupled with differential evolutionary algorithm. 13bench-mark test functions are used to check the algorithm performance and satisfied results are obtained. The algorithm is validated by optimizing a five-stage compressor. 1.979% and 2.5% improvement is obtained for total pressure and isentropic efficiency, respectively, while all the constraints are obeyed. 

Key words: Differential evolution; Stochastic ranking; Constrained optimization; Streamline curvature; Axial-flow compressor

摘要: 为了精确处理多级轴流压气机优化设计过程中的约束条件,提高优化设计可靠性,引入了随机排序微分进化算法。使用随机排序算法处理优化问题中普遍存在的约束条件,并将该算子与微分进化算法耦合。使用13个基准测试函数对算法进行了性能测试。测试结果表明该算法具有可观的精确性和稳定性。随后,对一弹用5级轴流压气机进行了优化设计,在满足约束的条件下,总压和等熵效率分别得到了1.979%和2.5%的效率提升。 

关键词: 微分进化;随机排序;约束优化;流线曲率法;轴流压气机 