Advances in verification and validation in computational fluid dynamics

被引:0
|
作者
Chen J. [1 ]
Xiao W. [1 ]
Zhao W. [1 ]
Zhang P. [1 ]
Yang F. [1 ]
Jin T. [1 ]
Guo Y. [1 ]
Wu X. [1 ]
Chen J. [1 ]
Wang R. [2 ]
Li L. [3 ]
机构
[1] China Aerodynamics Research and Development Centers, Sichuan, Mianyang
[2] Institute of Applied Physics and Computational Mathematics, Beijing
[3] Xi’an Aeronautics Computing Technique Research Institute, AVIC, Xi’an
关键词
calibration model experiment; error estimation; uncertainty quantification; verification and validation;
D O I
10.6052/1000-0992-23-012
中图分类号
学科分类号
摘要
Computational fluid dynamics (CFD) has played an increasingly important role in major engineering fields, and its credibility is the key constraint to its further extensive engineering application. It is widely accepted home and abroad that verification and validation is the only way to evaluate and guarantee the credibility of CFD. Through systematic verification and validation, the potential programming errors can be effectively identified, the reliability of numerical solving process can be guaranteed, the adequacy and prediction capability of mathematical models in the intended use can be objectively evaluated and improved when necessary. In this paper, with regard to two key issues, ‘what is verification and validation’ and ‘how to perform verification and validation’, the research progress of verification and validation in CFD is introduced from the aspects including basic concept, implementation processes, main methods, calibration model experiments and platform tools, with focusing on numerical error estimation and uncertainty quantification. At the end, the shortcomings of current research are reviewed and the key research directions are prospected. © 2023 Advances in Mechanics.
引用
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页码:626 / 660
页数:34
相关论文
共 143 条
  • [21] Assessment of experimental uncertainty with application to wind tunnel testing, (1999)
  • [22] Assessing experimental uncertainty supplement to AIAA S-071A-1999, (2003)
  • [23] Arendt P D, Apley D W, Chen W., Quantification of model uncertainty: calibration, model discrepancy, and identifiability, Journal of Mechanical Design, 134, (2012)
  • [24] Test uncertainty, (2005)
  • [25] Guide for verification and validation in computational solid mechanics, (2006)
  • [26] Standard for verification and validation in computational fluid dynamics and heat transfer, (2009)
  • [27] An illustration of the concepts of verification and validation in computational solid mechanics, (2012)
  • [28] Standard for verification and validation in computational solid mechanics, (2019)
  • [29] Andrianov G, Burriel S, Cambier S, Et al., OpenTURNS, an open source initiative to treat uncertainties, Risks'N statistics in a structured industrial approach, Proceedings of the ESREL’2007 Safety and Reliability Conference, (2007)
  • [30] Avdonin A, Polofke W., Quantification of the impact of uncertainties in operating conditions on the flame transfer function with nonintrusive polynomial chaos expansion, Journal of Engineering for Gas Turbines and Power, 141, (2019)