Regression analysis for thermal transport of fractional-order magnetohydrodynamic Maxwell fluid flow under the influence of chemical reaction using integrated machine learning approach,Chaos, Solitons & Fractals

当前位置： X-MOL 学术 › Chaos Solitons Fractals › 论文详情

Our official English website, www.x-mol.net, welcomes your feedback! (Note: you will need to create a separate account there.)

Regression analysis for thermal transport of fractional-order magnetohydrodynamic Maxwell fluid flow under the influence of chemical reaction using integrated machine learning approach
Chaos, Solitons & Fractals ( IF 5.3 ) Pub Date : 2024-12-19 , DOI: 10.1016/j.chaos.2024.115927
Waqar Ul Hassan, Khurram Shabbir, Ahmed Zeeshan, Rahmat Ellahi

An innovative idea of regression analysis based on machine learning technique for magnetohydrodynamic flow of Maxwell fluid within a cylinder is proposed. Mean Squared Error is used for the simulation of heat transfer and fluid flow. The governing flow equations involving a system of coupled, nonlinear fractional partial differential equations are solved by homotopic approach called HPM. The predicted solution is obtained with Python built-in code on Google-Colab. The effects of Atangana-Baleanu fractional time order derivative on the momentum, thermal, and concentration boundary layer are analyzed. It is observed that the momentum boundary layer gets higher and higher by increasing the values of Atangana-Baleanu fractional time order derivative. The thermal boundary layer shows improvement with the increasing value of the Peclet number. The concentration boundary layer thickness declines with the growing values of chemical reactions. The validation of results is examined by MSE, function fit, and correlation index.

更新日期：2024-12-19

点击分享查看原文

点击收藏

阅读更多本刊新发论文