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Mass-based nanofluid transport in decelerating separated-stagnation point flow over EMHD Riga plate: shape-factor effects and LMB-ANN prediction

Khadija RafiqueDepartment of Mathematics, University of Poonch, Rawalakot, AJK, PakistanZafar MahmoodCollege of Mechanical and Vehicle Engineering, Hunan University, Changsha, Hunan, 410082 PR ChinaIoan-Lucian PopaDepartment of Computing, Mathematics and Electronics, ‘’1 December 1918’’ University of Alba lulia, 510009 Alba lulia, RomaniaZilolakhon ChalaboyevaDepartment of General Chemistry, Kokand University Andijan branch, Andijan 170100, UzbekistanBobur MirzayevDepartment of Finance, Alfraganus University, Tashkent 100190, UzbekistanHamiden Abd El-Wahed KhalifaDepartment of Operations and Management Research, Faculty of Graduate Studies for Statistical Research, Cairo University, Giza 12613, EgyptMushtaq Ahmad AnsariDepartment of Pharmacology and Toxicology, College of Pharmacy, King Saud University, Riyadh, Saudi Arabia
2026en
ABI

Abstract

This research examines the unsteady, decelerating flow and thermal transfer of a mass-based nanofluid across an electromagnetic Riga plate, directly contrasting spherical and cylindrical nanoparticles. The base-fluid mass is set at 𝑤 𝑓 = 100 g, and the nanoparticle loading is defined by mass ( 𝑤 𝑠 = 2.5–10 g). Thermal radiation, viscous dissipation, wall mass suction, and electromagnetic forcing are integrated. The converted boundary-value problem is solved using MATLAB's bvp4c, and the obtained velocity and temperature data are learned using a Levenberg-Marquardt backpropagation artificial neural network (LMB-ANN). Elevating 𝑤 𝑠 from 2.5 to 10 g enhances the decreased skin-friction metric by 10.41% for spherical particles and 95.85% for cylindrical particles; concurrently, the reduced Nusselt number varies by +0.97% and −16.23%, respectively. Increasing the suction from S = 0.5 to 2.0 raises the Nusselt number by 158.79% and 162.41%, respectively, and increases skin friction by 58.24% (sphere) and 48.28% (cylinder). Electromagnetic forcing from Z=0.5 to 2.0 more than doubles the skin friction (116.49% and 116.56%) but lowers the heat transmission by 70%. Radiation elevates the overall radiative–conductive Nusselt number by 27.15% for spherical particles and by 25.70% for cylindrical particles. At large Eckert number, the Nusselt number for the spherical particle changes sign suggesting a dissipation-induced thermal overshoot and local heat-flux reversal. The LMB–ANN generates mean-square errors for training, validation, and testing ranging from 2.71×10⁻¹⁰ to 6.44×10⁻⁹, indicating a precise replication of the bvp4c solutions. These results demonstrate the potential of combining particle mass, shape, and electromagnetic control to tailor the wall drag and heat transmission. Elevating α from 0.5 to 2.0 amplifies skin friction by 87.46% and 122.72%, as well as the Nusselt number by 168.88% and 152.51% for spherical and cylindrical particles, respectively.

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