Novel artificial neural network approach for hybrid nanofluid flow over nonlinear permeable stretching sheets with Thomson and Troian boundary conditions
{"title":"Novel artificial neural network approach for hybrid nanofluid flow over nonlinear permeable stretching sheets with Thomson and Troian boundary conditions","authors":"Shazia Habib , Zeeshan Khan , Esraa N. Thabet , A.M. Abd-Alla , S.H. Elhag","doi":"10.1016/j.ijheatfluidflow.2024.109721","DOIUrl":null,"url":null,"abstract":"<div><div>The study investigates the flow of a hybrid nanofluid over a non-linear, permeable stretched sheet under Thomson and Troian boundary conditions, while also considering the Darcy-Forchheimer relationship. We employ the Cattaneo-Christov heat flux model and novel artificial neural networks for the first time. This paper describes a new way to use artificial neural networks to add carbon nanotubes to hybrid nanofluids with Thomson and Troian boundary conditions. This creates induced MHD. The MSE ranges from <span><math><mrow><msup><mn>10</mn><mrow><mo>-</mo><mn>08</mn></mrow></msup></mrow></math></span> to <span><math><mrow><msup><mn>10</mn><mrow><mo>-</mo><mn>09</mn></mrow></msup></mrow></math></span>. The AE range for all the cases lies around <span><math><mrow><msup><mn>10</mn><mrow><mo>-</mo><mn>03</mn></mrow></msup></mrow></math></span> to <span><math><mrow><msup><mn>10</mn><mrow><mo>-</mo><mn>07</mn></mrow></msup></mrow></math></span>. The value of mu is around <span><math><mrow><msup><mn>10</mn><mrow><mo>-</mo><mn>08</mn></mrow></msup></mrow></math></span>, while gradient ranges from <span><math><mrow><msup><mn>10</mn><mrow><mo>-</mo><mn>07</mn></mrow></msup></mrow></math></span> to <span><math><mrow><msup><mn>10</mn><mrow><mo>-</mo><mn>08</mn></mrow></msup></mrow></math></span>. This shows the high accuracy and precision of the proposed scheme. This research highlights the variation of different parameters with velocity, temperature and concentration. As the solid volume fraction rises, fluid velocity diminishes and temperature rises. Nanofluids exhibit enhancement with elevated inertial coefficient and Eckert number values. Increased inertial coefficient and Eckert number values correspond to rising temperatures. Concentration diminishes with rising solid volume percentage; yet, elevated activation energy results in enhanced concentration dispersion. It proves superior thermal conductivity and heat transmission capabilities, with future studies investigating the additional factors. Potential areas for further investigation include the study of other nanoparticles and different hybrid nanofluids and the investigation of real engineering challenges associated to heat and mass transfer in porous media. A graphic comparison between simple and hybrid nanofluids is presented. It is shown that the solid volume fraction improves the temperature distribution while decreasing the velocity profile. Furthermore, hybrid nanofluids perform better in heat transfer and have higher thermal conductivity than simple nanofluids.</div></div>","PeriodicalId":335,"journal":{"name":"International Journal of Heat and Fluid Flow","volume":"112 ","pages":"Article 109721"},"PeriodicalIF":2.6000,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Heat and Fluid Flow","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0142727X24004466","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MECHANICAL","Score":null,"Total":0}
引用次数: 0
Abstract
The study investigates the flow of a hybrid nanofluid over a non-linear, permeable stretched sheet under Thomson and Troian boundary conditions, while also considering the Darcy-Forchheimer relationship. We employ the Cattaneo-Christov heat flux model and novel artificial neural networks for the first time. This paper describes a new way to use artificial neural networks to add carbon nanotubes to hybrid nanofluids with Thomson and Troian boundary conditions. This creates induced MHD. The MSE ranges from to . The AE range for all the cases lies around to . The value of mu is around , while gradient ranges from to . This shows the high accuracy and precision of the proposed scheme. This research highlights the variation of different parameters with velocity, temperature and concentration. As the solid volume fraction rises, fluid velocity diminishes and temperature rises. Nanofluids exhibit enhancement with elevated inertial coefficient and Eckert number values. Increased inertial coefficient and Eckert number values correspond to rising temperatures. Concentration diminishes with rising solid volume percentage; yet, elevated activation energy results in enhanced concentration dispersion. It proves superior thermal conductivity and heat transmission capabilities, with future studies investigating the additional factors. Potential areas for further investigation include the study of other nanoparticles and different hybrid nanofluids and the investigation of real engineering challenges associated to heat and mass transfer in porous media. A graphic comparison between simple and hybrid nanofluids is presented. It is shown that the solid volume fraction improves the temperature distribution while decreasing the velocity profile. Furthermore, hybrid nanofluids perform better in heat transfer and have higher thermal conductivity than simple nanofluids.
期刊介绍:
The International Journal of Heat and Fluid Flow welcomes high-quality original contributions on experimental, computational, and physical aspects of convective heat transfer and fluid dynamics relevant to engineering or the environment, including multiphase and microscale flows.
Papers reporting the application of these disciplines to design and development, with emphasis on new technological fields, are also welcomed. Some of these new fields include microscale electronic and mechanical systems; medical and biological systems; and thermal and flow control in both the internal and external environment.