Evaluation of physics constrained data-driven methods for turbulence model uncertainty quantification-Reference-Cited by-同舟云学术

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Evaluation of physics constrained data-driven methods for turbulence model uncertainty quantification

Published:2023-04 Issue: Volume:255 Page:105837
ISSN:0045-7930
Container-title:Computers & Fluids
language:en
Short-container-title:Computers & Fluids

Author:

Matha Marcel^ORCID,Kucharczyk Karsten,Morsbach Christian^ORCID

Publisher

Elsevier BV

Subject

General Engineering,General Computer Science

Reference51 articles.

1. Quantifying uncertainty in CFD;Karniadakis;Trans ASME, J Fluids Eng,2002

2. Verification and validation in scientific computing;Oberkampf,2010

3. Estimating model-form uncertainty in Reynolds-averaged Navier–Stokes closures;Emory,2014

4. Quantification of model uncertainty in RANS simulations: A review;Xiao;Prog Aerosp Sci,2019

5. Needs and opportunities for uncertainty-based multidisciplinary design methods for aerospace vehicles;Zang,2002

Cited by 3 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

1. Physically constrained eigenspace perturbation for turbulence model uncertainty estimation;Physics of Fluids;2024-02-01

2. A Deep Learning Approach for Epistemic Uncertainty Quantification of Turbulent Flow Simulations;2024

3. Improved self-consistency of the Reynolds stress tensor eigenspace perturbation for uncertainty quantification;Physics of Fluids;2023-06-01

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