Non-intrusive reduced order modeling of unsteady flows using artificial neural networks with application to a combustion problem-Reference-Cited by-同舟云学术

Non-intrusive reduced order modeling of unsteady flows using artificial neural networks with application to a combustion problem

Published:2019-05 Issue: Volume:384 Page:289-307
ISSN:0021-9991
Container-title:Journal of Computational Physics
language:en
Short-container-title:Journal of Computational Physics

Author:

Wang Qian^ORCID,Hesthaven Jan S.^ORCID,Ray Deep^ORCID

Publisher

Elsevier BV

Subject

Computer Science Applications,Physics and Astronomy (miscellaneous),Applied Mathematics,Computational Mathematics,Modelling and Simulation,Numerical Analysis

Reference57 articles.

1. A survey of projection-based model reduction methods for parametric dynamical systems;Benner;SIAM Rev.,2015

2. Reduced Order Methods for Modeling and Computational Reduction, vol. 9;Quarteroni,2014

3. Certified Reduced Basis Methods for Parametrized Partial Differential Equations;Hesthaven,2016

4. Reduced basis method for the rapid and reliable solution of partial differential equations;Maday,2006

5. The proper orthogonal decomposition in the analysis of turbulent flows;Berkooz;Annu. Rev. Fluid Mech.,1993

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