Reduced order framework for convection dominant and pure diffusive problems based on combination of deep long short‐term memory and proper orthogonal decomposition/dynamic mode decomposition methods-Reference-Cited by-同舟云学术

Reduced order framework for convection dominant and pure diffusive problems based on combination of deep long short‐term memory and proper orthogonal decomposition/dynamic mode decomposition methods

Published:2020-09-20 Issue:3 Volume:93 Page:853-873
ISSN:0271-2091
Container-title:International Journal for Numerical Methods in Fluids
language:en
Short-container-title:Int J Numer Meth Fluids

Author:

Kherad Mahdi¹^ORCID,Moayyedi Mohammad Kazem²,Fotouhi Faranak¹

Affiliation:

1. Department of Computer Engineering and IT University of Qom Qom Iran

2. CFD, Turbulence and Combustion Research Lab., Department of Mechanical Engineering University of Qom Qom Iran

Publisher

Wiley

Subject

Applied Mathematics,Computer Science Applications,Mechanical Engineering,Mechanics of Materials,Computational Mechanics

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/fld.4911

Reference58 articles.

1. Comparative numerical analysis using reduced-order modeling strategies for nonlinear large-scale systems

2. Non-intrusive reduced order modelling with least squares fitting on a sparse grid

3. An efficient goal-based reduced order model approach for targeted adaptive observations

4. Reduced order modelling of an unstructured mesh air pollution model and application in 2D/3D urban street canyons

5. Design-space dimensionality reduction in shape optimization by Karhunen–Loève expansion

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