ISPH simulation and XGBoost prediction of double diffusion of NEPCM with sloshing fins under thermal radiation, Soret, and Dufour effects
Year: 2025
Type: article
Abstract: This work develops an integrated framework combining incompressible smoothed particle hydrodynamics (ISPH) and eXtreme Gradient Boosting (XGBoost) to analyze double-diffusive convection of nano-encapsulated phase change materials (NEPCM) in a porous cavity with sloshing fins under thermal radiation, Soret, and Dufour effects. A clear research gap is addressed by treating the coupled impact of dynamic sloshing fins, cross-diffusion (Soret–Dufour), and radiation in porous NEPCM systems topics commonly examined in isolation in prior studies thereby establishing the study’s novelty. The ISPH solver captures unsteady thermo-solutal transport, and XGBoost provides fast surrogate predictions of the average Nusselt and Sherwood numbers. Model credibility has been reinforced through benchmark validation for natural convection in porous enclosures and a particle-resolution independence study (variation ≤ 2% in Nu avg and Sh avg ). A fractional-time derivative is retained as a theoretical generalization for possible memory effects in porous/NEPCM media; it is not experimentally calibrated here and results are interpreted accordingly. Key trends indicate that increasing the Darcy number from 1 0 − 5 to 1 0 − 2 enhances Nu avg and Sh avg by about 36.2% and 28.4%, respectively, whereas raising the Hartmann number from 0 to 60 reduces them by 17.5% and 14.3%. Thermal radiation promotes heat transfer, with Nu avg increasing by 42.7% as Rd rises from 0 to 5. The trained XGBoost models, fitted to the validated ISPH database, reproduce target metrics with low errors, enabling rapid parametric screening. Main limitations include the two-dimensional setting, sinusoidal fin kinematics, and the absence of direct experiments; prospective extensions include 3D configurations, non-Newtonian NEPCM rheology, and active fin-control optimization.
Authors: Muhanna Ali H. Alrashdi, Azza M. Algatheem, Munirah Aali Alotaibi, Abdelraheem M. Aly
Language: English
Subfield: Mechanical Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $1,620
Awards: G5086076559, G8472158974
OpenAlex ID: W4416766908
