Project Details
Description
The funding supports Prof. Chen Junchao, Lishui University for the 6 months visit to Department of Mathematics and Information Technology, The Education University of Hong Kong. For research works in Hong Kong under this project, 1. The physics-informed neural networks (PINN) architectures for the incompressible 2D/3D magnetohydrodynamics (MHD) equations, 2. Forward problems in the PINN model of the incompressible 2D/3D MHD equations, 3. Inverse problems in the PINN model of the incompressible 2D/3D MHD equations.
Funding Source: HK Private Fund - Charities/Foundations^^
Funding Source: HK Private Fund - Charities/Foundations^^
| Status | Active |
|---|---|
| Effective start/end date | 11/12/25 → 10/06/26 |
UN Sustainable Development Goals
In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This project contributes towards the following SDG(s):
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SDG 9 Industry, Innovation, and Infrastructure
Keywords
- Incompressible fluid, Magnetohydrodynamics, PINN architectures, Forward problems, Inverse problems, 2-dimensional, 3-dimensional
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