Impact of cubic autocatalysis and infinite shear rate characteristics in MHD Carreau fluid over radiated bi-directional sheet; ANN-based computational scheme

• Thermal transport analysis in Non-Newtonian Carreau fluid over a bi-directional radiated stretching sheet. • Implementation of Carreau model to featuring non-Newtonian characteristics. • Incorporation of MHD and cubic autocatalysis in the physical model. • Development of a hybrid computational framework that incorporates bvp4c and (LM-ANN) scheme. • Effectiveness of emerging parameters on velocity and temperature via MATLAB illustrations statistical data. The implementation of advanced computational strategies for thermal transport analysis in fluid flow processes plays a significant role, which is crucial in modern thermal management systems. Artificial neural network (ANN) computational procedures play a vital role in solving the stiff nonlinear mathematical models due to their strong capability to train and predict data efficiently. The present endeavor delves into the discussion of heat transfer mechanism in Carreau fluid over a bi-directional stretching sheet, featuring magnetohydrodynamics (MHD), infinite shear rate characteristics and exhibiting cubic autocatalysis effect. In addition, magnetic effects are added to analyze the heat transfer efficiency and dual chemical reactions aid in convenient assessment of fluid concentration. Physical models generated partial differential equations (PDEs) are shifted into ordinary differential equations (ODEs) via introducing similarity variables. Computational analysis is made by employing a joint computational procedure i.e., bvp4c and Levenberg Marquardt neural network scheme (LM-NN). The results are displayed by different MATLAB illustrations and statistical data. The concentration field of Carreau fluid increased due to augmentation in diffusion parameter for both pseudoplasticity and dilatant region. Velocity profile intensified in both axial directions due to numeric growth in values of Weissenberg number and infinite shear rate parameter Uniform chemical reaction illustrates the motion of nanoparticles in the liquid, causing an increase in temperature during shear thinning and shear thickening due to the immersion of these particles in the base fluid.

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Publication Details

Journal
South African Journal of Chemical Engineering
Published
2025-01-09
DOI
https://doi.org/10.1016/j.sajce.2025.01.001
Citations
4
Primary Topic
Nanofluid Flow and Heat Transfer
Type
article
Field-Weighted Citation Impact
2.70
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article

Impact of cubic autocatalysis and infinite shear rate characteristics in MHD Carreau fluid over radiated bi-directional sheet; ANN-based computational scheme

Carlos William Atalaya Urrutia, Luis Jaime Collantes Santisteban, Hakim AL Garalleh, William Rolando Miranda Zamora et al.
4 citations
South African Journal of Chemical Engineering
Nanofluid Flow and Heat Transfer
2.70
article

Impact of cubic autocatalysis and infinite shear rate characteristics in MHD Carreau fluid over radiated bi-directional sheet; ANN-based computational scheme

Carlos William Atalaya Urrutia, Luis Jaime Collantes Santisteban, Hakim AL Garalleh, William Rolando Miranda Zamora, Fethi Mohamed Maiz, Adil Darvesh, Manuel Sánchez‐Chero, Hamiden Abd El-Wahed Khalifa
article en
4 citations

Abstract

• Thermal transport analysis in Non-Newtonian Carreau fluid over a bi-directional radiated stretching sheet. • Implementation of Carreau model to featuring non-Newtonian characteristics. • Incorporation of MHD and cubic autocatalysis in the physical model. • Development of a hybrid computational framework that incorporates bvp4c and (LM-ANN) scheme. • Effectiveness of emerging parameters on velocity and temperature via MATLAB illustrations statistical data. The implementation of advanced computational strategies for thermal transport analysis in fluid flow processes plays a significant role, which is crucial in modern thermal management systems. Artificial neural network (ANN) computational procedures play a vital role in solving the stiff nonlinear mathematical models due to their strong capability to train and predict data efficiently. The present endeavor delves into the discussion of heat transfer mechanism in Carreau fluid over a bi-directional stretching sheet, featuring magnetohydrodynamics (MHD), infinite shear rate characteristics and exhibiting cubic autocatalysis effect. In addition, magnetic effects are added to analyze the heat transfer efficiency and dual chemical reactions aid in convenient assessment of fluid concentration. Physical models generated partial differential equations (PDEs) are shifted into ordinary differential equations (ODEs) via introducing similarity variables. Computational analysis is made by employing a joint computational procedure i.e., bvp4c and Levenberg Marquardt neural network scheme (LM-NN). The results are displayed by different MATLAB illustrations and statistical data. The concentration field of Carreau fluid increased due to augmentation in diffusion parameter for both pseudoplasticity and dilatant region. Velocity profile intensified in both axial directions due to numeric growth in values of Weissenberg number and infinite shear rate parameter Uniform chemical reaction illustrates the motion of nanoparticles in the liquid, causing an increase in temperature during shear thinning and shear thickening due to the immersion of these particles in the base fluid.

South African Journal of Chemical EngineeringVol. 52
Cairo University (EG), Universidad Nacional de Piura (PE), Universidad Nacional Pedro Ruíz Gallo (PE), University of Business and Technology (SA), Universidad Señor de Sipán (PE), Universidad Nacional de Frontera, King Mongkut's University of Technology North Bangkok (TH), King Khalid University (SA)
Openalex Percentile: Top 12%
Nanofluid Flow and Heat Transfer
2.70
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