Exploration of Arrhenius activation energy and thermal radiation on MHD double-diffusive convection of ternary hybrid nanofluid flow over a vertical annulus with discrete heating
Shilpa B, V. Leela, Irfan Anjum Badruddin, Sarfaraz Kamangar, P. Ganesan, Abdul Azeem Khan
{"title":"Exploration of Arrhenius activation energy and thermal radiation on MHD double-diffusive convection of ternary hybrid nanofluid flow over a vertical annulus with discrete heating","authors":"Shilpa B, V. Leela, Irfan Anjum Badruddin, Sarfaraz Kamangar, P. Ganesan, Abdul Azeem Khan","doi":"10.1016/j.csite.2024.105593","DOIUrl":null,"url":null,"abstract":"The primary objective of this article is to examine the effect of discrete heating on MHD double-diffusive convection and thermal radiation of ternary hybrid nanofluid flow heat and mass transfer in a vertical cylindrical annulus along with Arrhenius activation energy and chemical reaction. In this study, the cavity inner wall has two distinct flush-mounted heat sources, while the outer wall is isothermally cooled at a lower temperature. The top and bottom walls are thermally insulated. The ensuing equations that govern the physical framework are solved using the implicit Crank-Nicholson finite difference technique. As the heater advances upward, the flow intensity decreases, leaving a part of the fluid static at the bottom of the cylinder. Because more heat induces high buoyant flow in the annulus, the absolute value of axial velocity and wall temperature rises as the length of the heat source rises. Enhancing the values of activation energy parameter drops the Arrhenius energy function, elevating the pace of the generative chemical process and hence the concentration. Increasing the thermal radiation parameter lowers the surface heat flux while enhancing the nanofluid temperature. The Brownian motion parameter corresponds to the random motion of nanoparticles in a fluid, and this irregular movement augments the collision of nanoparticles with fluid particles, causing the particle's kinetic energy which leads to thermal energy and hence increases temperature. Also, the heat and mass transfer characteristics are forecasted and analyzed by considering the Levenberg–Marquardt backpropagating artificial neural network technique.","PeriodicalId":9658,"journal":{"name":"Case Studies in Thermal Engineering","volume":"91 1","pages":""},"PeriodicalIF":6.4000,"publicationDate":"2024-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Case Studies in Thermal Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1016/j.csite.2024.105593","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"THERMODYNAMICS","Score":null,"Total":0}
引用次数: 0
Abstract
The primary objective of this article is to examine the effect of discrete heating on MHD double-diffusive convection and thermal radiation of ternary hybrid nanofluid flow heat and mass transfer in a vertical cylindrical annulus along with Arrhenius activation energy and chemical reaction. In this study, the cavity inner wall has two distinct flush-mounted heat sources, while the outer wall is isothermally cooled at a lower temperature. The top and bottom walls are thermally insulated. The ensuing equations that govern the physical framework are solved using the implicit Crank-Nicholson finite difference technique. As the heater advances upward, the flow intensity decreases, leaving a part of the fluid static at the bottom of the cylinder. Because more heat induces high buoyant flow in the annulus, the absolute value of axial velocity and wall temperature rises as the length of the heat source rises. Enhancing the values of activation energy parameter drops the Arrhenius energy function, elevating the pace of the generative chemical process and hence the concentration. Increasing the thermal radiation parameter lowers the surface heat flux while enhancing the nanofluid temperature. The Brownian motion parameter corresponds to the random motion of nanoparticles in a fluid, and this irregular movement augments the collision of nanoparticles with fluid particles, causing the particle's kinetic energy which leads to thermal energy and hence increases temperature. Also, the heat and mass transfer characteristics are forecasted and analyzed by considering the Levenberg–Marquardt backpropagating artificial neural network technique.
期刊介绍:
Case Studies in Thermal Engineering provides a forum for the rapid publication of short, structured Case Studies in Thermal Engineering and related Short Communications. It provides an essential compendium of case studies for researchers and practitioners in the field of thermal engineering and others who are interested in aspects of thermal engineering cases that could affect other engineering processes. The journal not only publishes new and novel case studies, but also provides a forum for the publication of high quality descriptions of classic thermal engineering problems. The scope of the journal includes case studies of thermal engineering problems in components, devices and systems using existing experimental and numerical techniques in the areas of mechanical, aerospace, chemical, medical, thermal management for electronics, heat exchangers, regeneration, solar thermal energy, thermal storage, building energy conservation, and power generation. Case studies of thermal problems in other areas will also be considered.