Heat transfer using Robin conditions in chemically reactive dual diffusive Casson nanofluid flow: An intelligent computing paradigm

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Abstract In this research-oriented study, dual diffusive Casson nanofluid stretching flow embedded in a Darcy-Forchheimer type porous medium is scrutinized using a quite new computerized neuro-heuristic optimization technique based on Ricker wavelet neural networks fabricated through global and local solvers namely genetic algorithms and sequential quadratic programming respectively. The flow of the suggested fluid model is characterized by thermal radiation, chemical reaction and Robin conditions for the analysis of heat and mass transfer effects. The similarity approach simplifies the governing partial differential equations of currently discussed flow model into a dimensionless nonlinear system of ordinary differential equations which are solved using the crafted solver and the obtained numerical outcomes are successfully compared with the reference solution compiled through Adam’s numerical technique. A detailed form convergence analysis of the novel design created solver is accomplished using various statistical performance operators.
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Heat transfer using Robin conditions in chemically reactive dual diffusive Casson nanofluid flow: An intelligent computing paradigm | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Heat transfer using Robin conditions in chemically reactive dual diffusive Casson nanofluid flow: An intelligent computing paradigm Zeeshan Ikram Butt, Iftikhar Ahmad, Muhammad Asif Zahoor Raja, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5370822/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 9 You are reading this latest preprint version Abstract In this research-oriented study, dual diffusive Casson nanofluid stretching flow embedded in a Darcy-Forchheimer type porous medium is scrutinized using a quite new computerized neuro-heuristic optimization technique based on Ricker wavelet neural networks fabricated through global and local solvers namely genetic algorithms and sequential quadratic programming respectively. The flow of the suggested fluid model is characterized by thermal radiation, chemical reaction and Robin conditions for the analysis of heat and mass transfer effects. The similarity approach simplifies the governing partial differential equations of currently discussed flow model into a dimensionless nonlinear system of ordinary differential equations which are solved using the crafted solver and the obtained numerical outcomes are successfully compared with the reference solution compiled through Adam’s numerical technique. A detailed form convergence analysis of the novel design created solver is accomplished using various statistical performance operators. Ricker wavelet Casson nanofluid Robin conditions Genetic algorithm Neural networks Sequential quadratic programming Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 04 Dec, 2024 Reviews received at journal 03 Dec, 2024 Reviews received at journal 03 Dec, 2024 Reviewers agreed at journal 02 Dec, 2024 Reviewers agreed at journal 01 Dec, 2024 Reviewers invited by journal 01 Dec, 2024 Editor assigned by journal 29 Nov, 2024 Submission checks completed at journal 01 Nov, 2024 First submitted to journal 01 Nov, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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