随机和认知不确定性框架下的CFD模型确认度量综述

夏侯唐凡; 陈江涛; 邵志栋; 吴晓军; 刘宇

doi:10.7527/S1000-6893.2021.25716

航空学报 >

2022 , Vol. 43 >Issue 8: 25716 - 025716

DOI: https://doi.org/10.7527/S1000-6893.2021.25716

综述

随机和认知不确定性框架下的CFD模型确认度量综述

夏侯唐凡 ,
陈江涛 ,
邵志栋 ,
吴晓军 ,
刘宇

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1. 电子科技大学机械与电气工程学院, 成都 611731;
2. 中国空气动力研究与发展中心计算空气动力研究所, 绵阳 621000;
3. 电子科技大学系统可靠性与安全性研究中心, 成都 611731

收稿日期: 2021-04-27

修回日期: 2021-08-18

网络出版日期: 2021-08-17

基金资助

国家数值风洞工程(NNW2020ZT7-B32)

收起

Model validation metrics for CFD numerical simulation under aleatory and epistemic uncertainty

XIAHOU Tangfan ,
CHEN Jiangtao ,
SHAO Zhidong ,
WU Xiaojun ,
LIU Yu

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1. School of Mechanical and Electrical Engineering, University of Electronic Science and Technology of China, Chengdu 611731, China;
2. Computational Aerodynamics Institute, China Aerodynamics Research and Development Center, Mianyang 621000, China;
3. Center for System Reliability and Safety, University of Electronic Science and Technology of China, Chengdu 611731, China

Received date: 2021-04-27

Revised date: 2021-08-18

Online published: 2021-08-17

Supported by

National Numerical Wind Tunnel Project (NNW2020ZT7-B32)

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摘要

随着计算机技术迅猛发展,计算流体力学(CFD)数值模拟技术已广泛应用于航空航天、船舶、风力、水利等领域,为装备的复杂流体分析、性能参数评估以及产品气动设计与优化提供重要验证与决策手段。现有的CFD技术都是在确定性的数学模型、物理参数、边界条件下进行数值模拟的。然而,由于物理过程的复杂性及人们的认知偏差,CFD技术中存在着模型参数、数值离散、模型形式等诸多不确定性因素且表征形式各异,给CFD数值模拟的可信度评估带来了极大挑战。文章阐述了CFD技术中面临的不确定性因素,探讨了主流模型确认度量方法的应用条件和适用范围。着重介绍在认知不确定性下的模型确认度量方法,包括几类重要的区间、概率盒下模型确认度量方法。通过NACA0012翼型绕流问题说明了CFD技术中考虑各种不确定性下的模型确认度量方法的有效性。

关键词： 计算流体力学(CFD); 数值模拟; 模型确认; 认知不确定性; 概率盒

本文引用格式

夏侯唐凡 , 陈江涛 , 邵志栋 , 吴晓军 , 刘宇 . 随机和认知不确定性框架下的CFD模型确认度量综述[J]. 航空学报, 2022 , 43(8) : 25716 -025716 . DOI: 10.7527/S1000-6893.2021.25716

Abstract

With the emergence of new computer technologies, Computational Fluid Dynamics (CFD) numerical simulation has been extensively implemented in many areas such as aerospace, national defense, ship hydrodynamics, wind power, and water conservancy. CFD numerical simulation provides effective decision-making and validation methods for complex fluid analysis of equipment, model parameter evaluation, and aerodynamic optimization design. Existing CFD simulations are conducted under the premises of deterministic mathematical models, fixed physical parameters, and fixed boundary conditions. Due to the complexity of physics and cognitive biases of human beings, there are, however, many potential uncertain factors with different representation forms in CFD, such as model parameter uncertainty, numerical dispersion, and model form uncertainty, resulting in a great challenge to the credibility of CFD simulation results. This article elaborates on the uncertain factors encountered in CFD, and provides a comprehensive discussion on the mainstream model validation metrics. We focus on the model validation metrics under epistemic uncertainty, including several metrics under the interval theory and probability-box theory. The NACA0012 airfoil flow problem is leveraged to demonstrate the effectiveness of the model validation metrics under various uncertainties in CFD.

Key words： Computational Fluid Dynamics (CFD); numerical simulation; model validation; epistemic uncertainty; probability-box

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