基于遗传算法的离心压缩机蜗壳参数化及多目标优化

doi:10.19799/j.cnki.2095-4239.2020.0413

储能科学与技术 ›› 2021, Vol. 10 ›› Issue (3): 1071-1079.doi: 10.19799/j.cnki.2095-4239.2020.0413

基于遗传算法的离心压缩机蜗壳参数化及多目标优化

李伟^1,²(), 左志涛^1,^2,³, 侯虎灿¹, 梁奇¹, 林志华^1,², 陈海生^1,^2,³()

^1.中国科学院工程热物理研究所，北京 100190
^2.中国科学院大学，北京 100049
^3.国家能源大规模物理储能技术(毕节)研发中心，贵州毕节 551712

收稿日期:2020-12-24 修回日期:2021-01-05 出版日期:2021-05-05 发布日期:2021-04-30
通讯作者: 陈海生 E-mail:liwei18@iet.cn;chen_hs@mail.etp.ac.cn
作者简介:李伟（1996—），男，硕士研究生，主要研究方向为叶轮机械气动热力学，E-mail：liwei18@iet.cn
基金资助:
国家重点研发计划项目(2017YFB0903605);中国科学院国际合作局国际伙伴计划项目(182211KYSB20170029);贵州省大规模物理储能工程技术研究中心(毕科合平台[2017]07号);贵州省大规模物理储能工程研究中心(黔发改高技[2017]951号)

Parameterization and multi-objective optimization of centrifugal compressor volute based on genetic algorithm

Wei LI^1,²(), Zhitao ZUO^1,^2,³, Hucan HOU¹, Qi LIANG¹, Zhihua LIN^1,², Haisheng CHEN^1,^2,³()

^1.Institute of Engineering Thermophysics, Chinese Academy of Sciences, Beijing 100190, China
^2.University of Chinese Academy of Sciences, Beijing 100049, China
^3.National Energy Large Scale Physical Energy Storage Technologies R&D Center (Bijie), Bijie 551712, Guizhou, China

Received:2020-12-24 Revised:2021-01-05 Online:2021-05-05 Published:2021-04-30
Contact: Haisheng CHEN E-mail:liwei18@iet.cn;chen_hs@mail.etp.ac.cn

摘要/Abstract

摘要：

排气蜗壳对离心压缩机的整体性能、工作范围有直接且不可忽视的影响。排气蜗壳由于其完全三维的、湍流的内部流动会引起蜗壳进口周向压力畸变，从而影响上游部件的流动稳定性。本工作针对先进压缩空气储能系统离心压缩机排气蜗壳进行多目标优化设计，提出了一种可变截面形状的参数化设计方法。以总压损失系数和静压恢复系数为优化目标变量，采用多个控制面和控制点的方式对离心压缩机蜗壳截面参数进行全周控制，结合最优拉丁超立方试验设计方法和全三维CFD数值方法生成样本空间，利用二代非支配排序遗传算法对Kriging近似模型进行多目标寻优，建立优化平台和优化方法。研究结果表明：优化后的截面形状能够减小通流截面旋涡中心的剪切应力，使排气蜗壳内部通流速度分布更加均匀；优化方案在设计工况下整级等熵效率提高了0.45%，压比提高了0.36%；与初始模型相比，优化后的排气蜗壳可以有效改善离心压缩机的整体性能。本研究有助于推动数值优化设计方法在离心压缩机排气蜗壳中的应用，为高性能、低总压损失离心压缩机的优化设计提供参考。

关键词: 离心压缩机, 排气蜗壳, 数值计算, 多目标优化

Abstract:

An outlet volute has a direct and non-negligible influence on the overall performance and working range of a centrifugal compressor. The complete three-dimensional turbulent internal flow of the outlet volute can cause a circumferential pressure distortion at the inlet of the volute, which directly affects the flow stability of the upstream components. In this paper, the multi-objective optimization design of the centrifugal compressor volute of a compressed-air energy storage system was performed, and a parameterized design method of variable cross-sectional shape was proposed. With the total pressure loss coefficient and static pressure recovery coefficient as optimization target variables, using multiple control surfaces and control points to control the cross-sectional shape of the centrifugal compressor volute and combining the optimal Latin hypercube experimental design method and the full three-dimensional computational fluid dynamics numerical method to generate the sample space, the second-generation non-dominated sorting genetic algorithm was used for multi-objective optimization of the Kriging approximation model, and an optimization platform and an optimization method were established. The results show that the optimized cross-section shape can reduce the shear stress in the vortex center and cause the uniform distribution of the meridional velocity in the outlet volute. In the design point, the overall isentropic efficiency and pressure ratio of the optimal design increased by 0.45% and 0.36%, respectively. Compared with the initial model, the volute with an optimized cross-sectional shape can improve the overall performance of the centrifugal compressor effectively. This research promotes the application of numerical optimization design method in the outlet volute of a centrifugal compressor and provides a reference for the optimal design of centrifugal compressors with high performance and low total pressure loss.

Key words: centrifugal compressor, outlet volute, numerical calculation, multi-objective optimization

中图分类号:

TH 452

李伟, 左志涛, 侯虎灿, 梁奇, 林志华, 陈海生. 基于遗传算法的离心压缩机蜗壳参数化及多目标优化[J]. 储能科学与技术, 2021, 10(3): 1071-1079.

Wei LI, Zhitao ZUO, Hucan HOU, Qi LIANG, Zhihua LIN, Haisheng CHEN. Parameterization and multi-objective optimization of centrifugal compressor volute based on genetic algorithm[J]. Energy Storage Science and Technology, 2021, 10(3): 1071-1079.

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参数	设计值
设计流量/kg·s^-1	5.31
压比	2.1
叶尖速度/m·s^-1	293
叶片数	20
额定转速/r·min^-1	14000
叶轮出口直径/mm	400
叶轮出口叶片角/(°)	90
叶顶间隙/mm	0.525
进口叶尖相对马赫数	0.65
扩压器出口位置/mm	680

项目	静压恢复系数C_p	总压损失系数K_p	等熵效率η/%	压比π
初始模型	0.6343	0.2847	87.73	2.471
优化最佳解	0.6683	0.2532	—	—
CFD数值验证	0.6693	0.2527	88.13	2.480

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基于遗传算法的离心压缩机蜗壳参数化及多目标优化

Parameterization and multi-objective optimization of centrifugal compressor volute based on genetic algorithm

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