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...
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| Autori principali: | , |
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| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
Elsevier
2025-09-01
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| Serie: | Case Studies in Thermal Engineering |
| Soggetti: | |
| Accesso online: | http://www.sciencedirect.com/science/article/pii/S2214157X25009256 |
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