A novel spatial-temporal prediction method for unsteady wake flows based on hybrid deep neural network-Reference-Cited by-同舟云学术

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A novel spatial-temporal prediction method for unsteady wake flows based on hybrid deep neural network

Published:2019-12-01 Issue:12 Volume:31 Page:127101
ISSN:1070-6631
Container-title:Physics of Fluids
language:en
Short-container-title:Physics of Fluids

Author:

Funder

Key Laboratory of Aerodynamics Noise Control

Program of Introducing Talents of Discipline to Universities

National Natural Science Foundation of China

The Key Laboratory of Reliability and Envrionment Engineering

Publisher

AIP Publishing

Subject

Condensed Matter Physics,Fluid Flow and Transfer Processes,Mechanics of Materials,Computational Mechanics,Mechanical Engineering

Link

http://aip.scitation.org/doi/pdf/10.1063/1.5127247

Reference32 articles.

1. Non-linear Petrov–Galerkin methods for reduced order hyperbolic equations and discontinuous finite element methods

2. Reduced-order modeling: new approaches for computational physics

3. Eigenmode Analysis in Unsteady Aerodynamics: Reduced Order Models

4. Dynamic mode decomposition of numerical and experimental data

5. Non-linear aeroelastic prediction for aircraft applications

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