Bio-Convection Effects of MHD Williamson Fluid Flow over a Symmetrically Stretching Sheet: Machine Learning
Author:
Priyadharshini P.1, Karpagam V.1, Shah Nehad Ali2, Alshehri Mansoor H.3ORCID
Affiliation:
1. Department of Mathematics, PSG College of Arts and Science, Coimbatore 641014, Tamil Nadu, India 2. Department of Mechanical Engineering, Sejong University, Seoul 05006, Republic of Korea 3. Department of Mathematics, College of Science, King Saud University, P.O. Box 2455, Riyadh 11451, Saudi Arabia
Abstract
The primary goal of this research study is to examine the influence of Brownian motion and thermophoresis diffusion with the impact of thermal radiation and the bioconvection of microorganisms in a symmetrically stretching sheet of non-Newtonian typical Williamson fluid. Structures of the momentum, energy, concentration, and bio-convection equations are interconnected with the imperative partial differential equations (PDEs). Similarity transformations are implemented to translate pertinent complicated partial differential equations into ordinary differential equations (ODEs). The BVP4C approach from the MATLAB assemblage computational methods scheme is extensively impacted by the results of these ODEs. The impact of several physical parameters, including Williamson fluid We(0.2≤We≤1.2), the magnetic field parameter M(0.0≤M≤2.5), Brownian motion Nb(0.0≤Nb≤1.0), thermophoresis diffusion Nt(0.1≤Nt≤0.9). In addition, various physical quantities of the skin friction (RexCfx), Nusselt number (Nux), Sherwood number (Shx), and motile microorganisms (Nnx) are occupied and demonstrate the visualization of graphs and tabular values. These outcomes are validated with earlier obtained results, displaying excellent synchronicity in the physical parameters. Furthermore, the physical quantities concerning the non-dimensional parameters are anticipated by employing Multiple Linear Regression (MLR) in Machine Learning (ML) as successfully executed a novelty of this study. These innovative techniques can help to advance development and technologies for future researchers. The real-world implications of this research are that bio-remediation, microbial movements in mixed fluids, and cancer prevention therapy are crucial.
Funder
Researchers Supporting Project King Saud University, Riyadh, Saudi Arabia
Subject
Physics and Astronomy (miscellaneous),General Mathematics,Chemistry (miscellaneous),Computer Science (miscellaneous)
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