离心压缩机性能预测中雷诺平均湍流模型的不确定度量化与分析

王同生; 席光; 孙中国; 张晨庆; 李安娜; 黄柱

doi:10.7652/xjtuxb202509018

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离心压缩机性能预测中雷诺平均湍流模型的不确定度量化与分析

—————————————————————— | 更新时间：2025-09-11

- 离心压缩机性能预测中雷诺平均湍流模型的不确定度量化与分析
- Uncertainty Quantification of Reynolds-Averaged Navier-Stokes Turbulence Model in Predicting Centrifugal Compressor Performance
- 西安交通大学学报 2025年59卷第9期页码：187-196
- 作者机构：
  
  西安交通大学能源与动力工程学院， 710049，西安
- 作者简介：
  
  王同生（1992—），男，助理教授
  黄柱，男，副教授，博士生导师。
- 基金信息：
  
  国家自然科学基金资助项目(52206053;52130603;12102331)
- DOI：10.7652/xjtuxb202509018
  中图分类号： TK05
- 收稿：2025-03-11，
  
  网络首发：2025-04-15，
  
  纸质出版：2025-09-10
- 稿件说明：
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王同生, 席光, 孙中国, 等. 离心压缩机性能预测中雷诺平均湍流模型的不确定度量化与分析[J]. 西安交通大学学报, 2025,59(9):187-196.

WANG Tongsheng, XI Guang, SUN Zhongguo, et al. Uncertainty Quantification of Reynolds-Averaged Navier-Stokes Turbulence Model in Predicting Centrifugal Compressor Performance[J]. Journal of Xi’an Jiaotong University, 2025, 59(9): 187-196.
王同生, 席光, 孙中国, 等. 离心压缩机性能预测中雷诺平均湍流模型的不确定度量化与分析[J]. 西安交通大学学报, 2025,59(9):187-196. DOI： 10.7652/xjtuxb202509018.

WANG Tongsheng, XI Guang, SUN Zhongguo, et al. Uncertainty Quantification of Reynolds-Averaged Navier-Stokes Turbulence Model in Predicting Centrifugal Compressor Performance[J]. Journal of Xi’an Jiaotong University, 2025, 59(9): 187-196. DOI： 10.7652/xjtuxb202509018.

摘要

采用雷诺平均Navier-Stokes（RANS）湍流模型预测离心压缩机的气动性能往往与实验测量结果存在显著差异。为量化RANS模型对离心压缩机性能预测的不确定度，通过对可实现且物理约束的雷诺应力张量特征值和特征向量进行扰动，即在质心图内通过非均匀扰动方法将基础流动扰动至湍流的3个极限状态，以获得湍流输运方程生成项的极值，进而量化RANS模型中的L2不确定度。在离心压缩机性能曲线左端的可用工况下，施加扰动后湍流模型预测的总压比和多变效率的置信区间基本覆盖了整个工况范围内的实验结果，不施加扰动时的数值预测和实验结果之间的最大总压比偏差为4.37%和最大多变效率偏差为0.9%。进一步探究了不同扰动对离心叶轮叶片吸力面流动分离发生位置的影响规律，结果显示：雷诺应力张量单组分的特征值扰动对流动分离预测较保守，而单组分特征向量扰动的预测则较激进。RANS模型的不确定度对气动性能边界的预测可进一步用于实验测量数据的交叉验证。

Abstract

The prediction of the aerodynamic performance of a centrifugal compressor using the Reynolds-averaged Navier-Stokes (RANS) turbulence model often shows significant discrepancies with experimental results. To quantify the uncertainty of RANS models in predicting centrifugal compressor performance

the eigenvalues and eigenvectors of the realizable

physically constrained Reynolds stress tensor are perturbed. Specifically

a non-uniform perturbation method is applied within the barycentric triangle to disturb the base flow toward the three limiting states of turbulence

thereby obtaining the extrema of the production terms in the turbulence transport equations. This approach enables the quantification of the L2 uncertainty in the RANS model. At operating conditions on the left of the performance curve

the confidence interval fully encompasses the maximum deviations of 4.37% in total pressure ratio and 0.9% in polytropic efficiency observed between the unperturbed simulation and experimental results. Besides

the influence of different perturbations on predicting flow separation onset on the suction surface of a centrifugal impeller blade is investigated. The results indicate that eigenvalue perturbations of a single component of the Reynolds stress tensor yield more conservative predictions of flow separation

whereas eigenvector perturbations of a single component result in more aggressive predictions. The uncertainty in the RANS model's predictions of performance boundaries can further be utilized for cross-validation with experimental measurement data.

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references

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