Hybrid incompressible SPH–machine learning approach for simulating natural convection in a porous intricate domain
This study explores the double-diffusive convection of nano-enhanced phase change material (NEPCM) inside a intricate-shaped cavity partially filled with porous media, integrating Incompressible Smoothed Particle Hydrodynamics (ISPH) with an Artificial Intelligence (AI)-based predictive model. The n...
Saved in:
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-09-01
|
| Series: | Case Studies in Thermal Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2214157X25009256 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|