Comparative Analysis of Artificial Neural Networks and Response Surface Methods for Mixed Convective Heat Transfer in a Rectangular Channel with Heated Diamond-Shaped Obstacles

Document Type : Research Paper

Authors
Department of Computer Science and Engineering, Stamford University, Bangladesh
Abstract
The mixed convective heat transfers and flow characteristics of a non-Newtonian power-law hybrid nanofluid, Al2O3-CNT/water) in an open rectangular channel containing two heated diamond-shaped blocks with a bottom inlet, two top outlets, and isothermal cold side walls, are investigated numerically. The non-dimensional controlling transport equations are computed numerically using COMSOL Multiphysics, while the left vertical wall is kept at an identical cold temperature (Tc). The analysis considers a wide range of controlling parameters: nanoparticle volume fraction (ϕ = 0.00, 0.01, 0.02, 0.04), Richardson number (Ri = 1.0, 2.0, 4.0, 6.0), Reynolds number (Re = 50, 100, 200, 400), Power law index (n = 0.6, 0.8, 1.0, 1.2), and inlet/outlet width (Win = Wout = 0.1). The results exhibit that the governing parameters have a substantial effect on the thermal performance of the rectangular channel: higher values of the power-law index (n) reduced heat transfer, while higher values of the nanoparticle volume fraction (ϕ), Richardson number (Ri), and Reynolds number (Re) increase it. While comparative analyses using Response Surface Methodology (RSM) and Artificial Neural Networks (ANNs) confirm their efficacy in accurately predicting the average Nusselt number, Nuav detailed flow and thermal characteristics are presented, providing effective tools for designing and optimizing of hybrid nanofluid-based thermal systems.
Keywords
Subjects

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