Neural network study of gyrotactic microorganism dynamics in nanofluid through porous stretched surface
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27740%2F25%3A10258819" target="_blank" >RIV/61989100:27740/25:10258819 - isvavai.cz</a>
Result on the web
<a href="https://www.sciencedirect.com/science/article/pii/S2590123025039106?via%3Dihub" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2590123025039106?via%3Dihub</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1016/j.rineng.2025.107858" target="_blank" >10.1016/j.rineng.2025.107858</a>
Alternative languages
Result language
angličtina
Original language name
Neural network study of gyrotactic microorganism dynamics in nanofluid through porous stretched surface
Original language description
In this article, the effects of swimming gyrotactic microorganisms on magnetohydrodynamic nanofluid flow through a porous medium governed by Darcy-Forchheimer law are investigated. The nonlinear coupled mathematical model is solved using a hybrid algorithm that combines MATLAB's bvp4c solver with the Levenberg-Marquardt technique (LMT). The proposed LMT-based neural network model exhibits excellent agreement with the reference solutions, achieving extremely low mean squared error (MSE) values of 10-10, confirming its robustness and efficient convergence. The reliability of the proposed hybrid methodology is confirmed through excellent agreement between neural network predictions and numerical solutions. Parametric studies indicate that the velocity profile F '(eta) enhances with higher motile microorganism parameter (Nr) and bioconvection Rayleigh number (Rb), but declines with increasing Darcy permeability parameter (beta D) and magnetic parameter M. Temperature theta(eta) rises with thermophoresis (Nt), Brownian motion (Nb), Eckert number (Ec) and magnetic parameter M, while decreasing for larger Prandtl number (Pr). The nanoparticle concentration chi(eta) is diminished for higher Schmidt (Sc) and Brownian motion (Nb) parameters, whereas it is augmented under stronger thermophoretic effects (Nt). Similarly, the motile microorganism profile chi(eta) is suppressed by larger microorganism Schmidt number (Scm), P & eacute;clet number (Pe), and microorganism concentration difference ratio (Omega d), indicating reduced motile microorganism density under these conditions. These results demonstrate the effectiveness of the hybrid bvp4c-LMT framework in accurately capturing complex nonlinear transport and bioconvective dynamics in gyrotactic nanofluids.
Czech name
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Czech description
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Classification
Type
J<sub>imp</sub> - Article in a specialist periodical, which is included in the Web of Science database
CEP classification
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OECD FORD branch
21100 - Other engineering and technologies
Result continuities
Project
<a href="/en/project/EH23_021%2F0008759" target="_blank" >EH23_021/0008759: Increasing the resilience of power grids in the context of decarbonisation, decentralisation and sustainable socio-economic development</a><br>
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Results in Engineering
ISSN
2590-1230
e-ISSN
2590-1230
Volume of the periodical
28
Issue of the periodical within the volume
December
Country of publishing house
NL - THE KINGDOM OF THE NETHERLANDS
Number of pages
22
Pages from-to
107858
UT code for WoS article
001607629700005
EID of the result in the Scopus database
2-s2.0-105020859160