Rapid Prediction of Compressor Rotating Stall Inception Using Arnoldi Eigenvalue Algorithm

Author:

Fang Yibo1,Sun Dakun1,Xu Dengke1,He Chen2,Sun Xiaofeng1

Affiliation:

1. Beihang University, 100191 Beijing, People’s Republic of China

2. China Aerodynamics Research and Development Center, 621000 Mianyang, People’s Republic of China

Abstract

This paper presents a stability model that can make a rapid prediction of the rotating stall inception in turbomachinery and provide the spatial distribution of the corresponding instability mode. In addition, this model can take the three-dimensional geometry of blades and complex flow details in the compressor into consideration, and the solution of the development process of small perturbations can be converted to a nonlinear eigenvalue problem. We propose a solution method by converting the nonlinear eigenvalue problem into a generalized one; then, it can be solved by the Arnoldi algorithm. The proposed method can shorten the elapsed time from hundreds of hours to a few minutes, as compared with the methods adopted in previous works, substantially reducing the computational cost. Furthermore, the spatial distribution of eigenvectors can be obtained to investigate the characteristics of the perturbation mode, which can be applied as a foundation to set the inlet/outlet boundary conditions and select the eigenvalue representing the rotating stall inception. In the cases of a transonic isolated rotor and a subsonic one-stage compressor, the results are in accordance with those measured in experiments, verifying the accuracy and effectiveness of the stability model. Therefore, the model can be applied to evaluate the flow stability in the design stage of compressors with low computational cost.

Funder

the Key Laboratory of Pre-Research Management Center

National Science and Technology Major Project

Science Center for Gas Turbine Project

Publisher

American Institute of Aeronautics and Astronautics (AIAA)

Subject

Aerospace Engineering

Cited by 2 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3