Double Diffusion Convection in Sisko Nanofluids with Thermal Radiation and Electroosmotic Effects: A Morlet-Wavelet Neural Network Approach

Arshad Riaz^1,*, Misbah Ilyas¹, Muhammad Naeem Aslam², Safia Akram³, Sami Ullah Khan⁴, Ghaliah Alhamzi⁵
1 Department of Mathematics, Division of Science and Technology, University of Education, Lahore, 54770, Pakistan
2 Department of Mathematics, Lahore Garrison University, Lahore, 54000, Pakistan
3 MCS, National University of Sciences and Technology, Islamabad, 44000, Pakistan
4 Department of Mathematics, Namal University, Mianwali, 42250, Pakistan
5 Department of Mathematics and Statistics, College of Science, Imam Mohammad Ibn Saud Islamic University (IMSIU), Riyadh, 11432, Saudi Arabia
* Corresponding Author: Arshad Riaz. Email: email
(This article belongs to the Special Issue: Mathematical and Computational Modeling of Nanofluid in Biofluid Systems)

Computer Modeling in Engineering & Sciences https://doi.org/10.32604/cmes.2025.072513

Received 28 August 2025; Accepted 11 November 2025; Published online 02 December 2025

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Abstract

Peristaltic transport of non-Newtonian nanofluids with double diffusion is essential to biological engineering, microfluidics, and manufacturing processes. The authors tackle the key problem of Sisko nanofluids under double diffusion convection with thermal radiations and electroosmotic effects. The study proposes a solution approach by using Morlet-Wavelet Neural Networks that can effectively solve this complex problem by their superior ability in the capture of nonlinear dynamics. These convergence analyses were calculated across fifty independent runs. Theil’s Inequality Coefficient and the Mean Squared Error values range from 10⁻⁷ to 10⁻⁵ and 10⁻⁷ to 10⁻¹⁰, respectively. These values showed the proposed method is scientifically reliable and fast converging. Studies reveal that the intensity of the magnetic field causes a reduction in the flow velocity profile in the center of the channel. It is also evaluated that thermal radiations enhance the energy of the system, which promotes thermally induced diffusion and particle flow. The physical applications of this work pertain to improving fluid flow and heat transfer in engineering structures like converters or cooling devices or magnetic fluids in electronics, energy, and biomedical applications, where optimal control of fluid behavior is of paramount importance.