An Invariant and Highly–Accurate Strategy for Data-Driven Turbulence Modelling-Reference-Cited by-同舟云学术

An Invariant and Highly–Accurate Strategy for Data-Driven Turbulence Modelling

Published:2022 Issue: Volume: Page:
ISSN:1556-5068
Container-title:SSRN Electronic Journal
language:en
Short-container-title:SSRN Journal

Author:

Brener Bernardo P.,Cruz Matheus A.,Macedo Matheus S. S.,Thompson Roney Leon

Publisher

Elsevier BV

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference72 articles.

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3. Data-driven decomposition of the streamwise turbulence kinetic energy in boundary layers. part 2. Integrated energy and data-driven decomposition of the streamwise turbulence kinetic energy in boundary layers;W J Baars;J. Fluid Mech,2020

4. Essai sur la theorie des eaux curantes;J Boussinesq;Mem. Pres. Acad. Sci,1877

5. Conditioning and accurate solutions of RANS equations with data-driven turbulence closures;B P Brener;J. Fluid Mech,2021

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1. On the Generalizability of Machine-Learning-Assisted Anisotropy Mappings for Predictive Turbulence Modelling;International Journal of Computational Fluid Dynamics;2022-08-09

2. Pre-processing DNS data to improve statistical convergence and accuracy of mean velocity fields in invariant data-driven turbulence models;Theoretical and Computational Fluid Dynamics;2022-03-21