“A Physics-Informed Neural Networks framework for simulating natural convection of Cu–water micropolar nanofluid in a porous enclosure with internal heat generation”
The paper has been published in the European Journal of Mechanics / B Fluids.
In this work, we develop a Physics-Informed Neural Network (PINN) framework for a strongly coupled heat-transfer and fluid-flow problem involving micropolar nanofluids in porous media. The approach combines Fourier feature encoding with adaptive loss weighting and is validated against meshless RBF-FD solutions. The results also provide insights into the effects of internal heat generation, porosity, vortex viscosity, and nanoparticle concentration on heat-transfer performance.
I am very happy to see this work published and grateful for the collaboration and effort behind it.
Authors: Marzieh Biglari and Vahid Reza Hosseini
DOI: https://doi.org/10.1016/j.euromechflu.2026.204633
Link: https://www.researchgate.net/publication/413763098_A_Physics-Informed_N…
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