Impact of different arrangements of heated elliptical body, fins and differential heater in MHD convective transport phenomena of inclined cavity utilizing hybrid nanoliquid: Artificial neutral network prediction

Abstract

In the current scenario, the impact of different arrangements of solid heated elliptical body, discrete heater (LH/H), array of fins with different sizes (1×2, 2×1, 2×2), conductivity ratio (r), magnetic field (Hartmann number, Ha), angle of inclination (β), nanoparticle volume fraction (χ) and Rayleigh number (Ra) is investigated for natural transport phenomena in the cavity containing hybrid nanoliquid. The cavity consists of three equally spaced fins on one wall and heated elliptical body inside the cavity. The homogeneous hybrid nanoliquid (Al2O3-Cu/water) model using experimental data is utilized and results are evaluated for different controlling parameters: Rayleigh numbers (Ra=103 to 106), Hartmann number (Ha=0 to 100), discrete heater (LH/H=0.1 to 0.9), angle of elliptical body (ω=0° to 180°) with three different positions (Center, POS I and II), angle of inclination (β=0 to π), thermal conductivity ratio (r=0.01–100), nanoparticle volume fraction (χ=0 to 0.02) using Galerkin Finite Element Method (GFEM). The mesh grid independency test is also performed for different combinations of meshes and a refined mesh with optimal degrees of freedom (DoFs=190275) has been considered for entire convection range (Ra=103−106).The impact of controlling parameters on average Nusselt number evaluated from the numerical heat transfer analysis has been compared and predicted using feed forward neural network model. The Levenberg-Marquardt back propagation algorithm is used for ANN training based on limited simulated data with optimal number of neurons and average R2 of 0.99988. The quadratic regression model, which is also determined using the MATLAB built-in subroutine ’fitlm’, demonstrates the greatest dependency of Nusselt number on nanoparticle concentration.