Modeling Non‐Stationary Wind‐Induced Fluid Motions With Physics‐Informed Neural Networks for the Shallow Water Equations in a Polar Coordinate System

Modeling Non‐Stationary Wind‐Induced Fluid Motions With Physics‐Informed Neural Networks for the Shallow Water Equations in a Polar Coordinate System

Abstract Physics‐informed neural networks (PINNs) are increasingly being used in various scientific disciplines. However, dealing with non‐stationary physical processes remains a significant challenge in such models, whereas fluid motions are typically non‐stationary. In this study, a PINN‐based met...

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Bibliographic Details
Main Authors: Zaiyang Zhou, Yu Kuai, Jianzhong Ge, Bas vanMaren, Zhenwu Wang, Kailin Huang, Pingxing Ding, Zhengbing Wang
Format: Article
Language:English
Published: Wiley 2025-01-01
Series:Water Resources Research
Subjects:
PINN
shallow water equation
polar coordinate
non‐stationary
boundary discontinuity
hybrid model
Online Access:https://doi.org/10.1029/2024WR037490
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https://doi.org/10.1029/2024WR037490

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