Spatial artificial neural network model for subgrid-scale stress and heat flux of compressible turbulence
Authors:
- Chenyue XieCXChenyue Xie
- Jianchun WangJianchun Wang
- Hui LiHLHui Li
- Minping WanMinping Wan
- Shiyi ChenSCShiyi Chen
Open Access
- 1 January 2020
- journal article
- research article
- Published by Elsevier in Theoretical and Applied Mechanics Letters
- Vol. 10 (1) , 27-32
Abstract
No abstract availableKeywords
Funding Information
- Science, Technology and Innovation Commission of Shenzhen Municipality (KQTD20180411143441009, JCYJ20170412151759222, ZDSYS201802081843517)
- Southern University of Science and Technology
- China Academy of Space Technology (2016QNRC001)
- National Natural Science Foundation of China (91752201, 91952104, 11702127)
This publication has 37 references indexed in Scilit:
- Reynolds-stress-constrained large-eddy simulation of wall-bounded turbulent flowsJournal of Fluid Mechanics, 2012
- Effect of shocklets on the velocity gradients in highly compressible isotropic turbulencePhysics of Fluids, 2011
- A hybrid numerical simulation of isotropic compressible turbulenceJournal of Computational Physics, 2010
- Locality of turbulent cascadesPhysica D: Nonlinear Phenomena, 2005
- Ten questions concerning the large-eddy simulation of turbulent flowsNew Journal of Physics, 2004
- Large Eddy Simulation and the variational multiscale methodComputing and Visualization in Science, 2000
- Monotonicity Preserving Weighted Essentially Non-oscillatory Schemes with Increasingly High Order of AccuracyJournal of Computational Physics, 2000
- Scale-Invariance and Turbulence Models for Large-Eddy SimulationAnnual Review of Fluid Mechanics, 2000
- On the properties of similarity subgrid-scale models as deduced from measurements in a turbulent jetJournal of Fluid Mechanics, 1994
- Compact finite difference schemes with spectral-like resolutionJournal of Computational Physics, 1992