Artificial Neural Network Prediction for Thermal Characteristics of Nanofluid over a Stretching Sheet with Variable Properties

Saman Iftikhar; Atifa Latif; Taha Azam; Ayesha Bibi

Authors

Saman Iftikhar Faculty of Computer Studies, Arab Open University, Saudi Arabia
Atifa Latif GC University Faisalabad
Taha Azam Government College University Faisalabad Pakistan
Ayesha Bibi Government College University Faisalabad Pakistan

Keywords:

Bvp4c Approach, Artificial Neural Network, Levenberg Marquardt Technique with Back Propagations, Nano Fluid, Heat Transfer, Variable Flow Properties, Stretching Sheet, Stagnation Point

Abstract

Stagnation-point heat transmission is one such crucial phenomenon taking place in various industrial and technical processes, particularly those involving stretched surfaces. In this study the heat transfer qualities of nanofluids flow towards a stretched sheet under boundary conditions at stagnation point with variable thermophysical properties have been investigated using an ANN framework. Compared to conventional fluids, nanofluids which consist of a base fluid and suspended nanoparticles perform better in heat transmission and have a higher thermal conductivity. The mathematical model in the form of governing partial differential equations has been obtained and transformed into nonlinear ordinary differential equations using the appropriate similarity transformations. These differential equations have subsequently been solved using the appropriate numerical techniques in BVP4c solver in MATLAB. In order to describe and forecast the heat transfer behavior of nanofluids close to a stretching sheet with variable thermophysical properties, the current study explores the use of Artificial Neural Networks (ANN) in physical problems. The impact of important parameters such as the stretching parameter, Prandtl number, nanoparticle volume fraction, and variable property parameters on the velocity and temperature profiles is examined. The ANN model has been trained using the numerical solutions obtained from MATLAB BVP4c. It was observed that the heat transfer performance improves by increasing the nanoparticle concentration. The numerical findings have compared the trained network predicts velocity profile, temperature field and concentration with minimum inaccuracy. The work demonstrates improvements in thermal systems that incorporate nanofluids on stretched surfaces with potential utilizations in cooling technologies.

Author Biographies

Saman Iftikhar, Faculty of Computer Studies, Arab Open University, Saudi Arabia

Associate Professor in Computer Sciences

Taha Azam, Government College University Faisalabad Pakistan

Research Scholar

Ayesha Bibi, Government College University Faisalabad Pakistan

Research Scholar

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