Multi-Order Loss Functions For Accelerating Unsteady Flow Simulations with Physics-Based AI-Reference-Cited by-同舟云学术

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Multi-Order Loss Functions For Accelerating Unsteady Flow Simulations with Physics-Based AI

Published:2024-06-25 Issue: Volume:31 Page:940-946
ISSN:
Container-title:2024 IEEE Conference on Artificial Intelligence (CAI)
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Author:

Lim Wei Xian¹,Arafat Naheed Anjum¹,Chan Wai Lee²,Kong Wai-Kin Adams³

Affiliation:

1. Nanyang Technological University (NTUsg),Rolls-Royce@NTU Corporate Lab,Singapore

2. Nanyang Technological University (NTUsg),School of Mechanical and Aerospace Engineering (MAE),Singapore

3. Nanyang Technological University (NTUsg),College of Computing and Data Science (CCDS),Singapore

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10605128/10605229/10605343.pdf?arnumber=10605343

Reference26 articles.

1. Enhancing computational fluid dynamics with machine learning

2. Analytical theories of turbulence

3. A numerical study of three-dimensional turbulent channel flow at large Reynolds numbers

4. Solutions of Reynolds-averaged Navier-Stokes equations for three-dimensional incompressible flows

5. Machine learning–accelerated computational fluid dynamics

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