Impact of Arrhenius activation energy on magnetic nanofluid flow over a slendering stretchable sheet with nonlinear radiative heat transfer: A machine learning algorithm

IF 1.7 4区工程技术 Q3 MECHANICS

Numerical Heat Transfer Part B-Fundamentals Pub Date : 2024-04-04 DOI:10.1080/10407790.2024.2333942

S.R.R. Reddy, K. R. Sekhar, Sunil Kumar Charupalli, Shaik Jakeer, M. Lakshmi Rupa, K. Manikandan, T. Mahesh Kumar

引用次数: 0

Abstract

Thermal systems in the contemporary world need effective cooling and heating methods. Heat transfer technology plays a vital role in various industries, including aerospace, electronic equipment, a...

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阿伦尼乌斯活化能对具有非线性辐射传热的可拉伸滑片上的磁性纳米流体流动的影响：一种机器学习算法

当今世界的热系统需要有效的冷却和加热方法。热传导技术在各行各业都发挥着至关重要的作用，包括航空航天、电子设备、汽车、航空航天、航空航天设备、航空航天设备、航空航天设备、航空航天设备...

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Numerical Heat Transfer Part B-Fundamentals 工程技术-力学

CiteScore

2.40

自引率

0.00%

发文量

审稿时长

2.8 months

期刊介绍： Published 12 times per year, Numerical Heat Transfer, Part B: Fundamentals addresses all aspects of the methodology for the numerical solution of problems in heat and mass transfer as well as fluid flow. The journal’s scope also encompasses modeling of complex physical phenomena that serves as a foundation for attaining numerical solutions, and includes numerical or experimental results that support methodology development. All submitted manuscripts are subject to initial appraisal by the Editor, and, if found suitable for further consideration, to peer review by independent, anonymous expert referees. The Editor reserves the right to reject without peer review any papers deemed unsuitable.