Colección SciELO Chile

Departamento Gestión de Conocimiento, Monitoreo y Prospección
Consultas o comentarios: productividad@anid.cl
Búsqueda Publicación
Búsqueda por Tema Título, Abstract y Keywords



Artificial neural network analysis of Jeffrey hybrid nanofluid with gyrotactic microorganisms for optimizing solar thermal collector efficiency
Indexado
WoS WOS:001416645600029
Scopus SCOPUS_ID:85218189514
DOI 10.1038/S41598-025-88877-6
Año 2025
Tipo artículo de investigación

Citas Totales

Autores Afiliación Chile

Instituciones Chile

% Participación
Internacional

Autores
Afiliación Extranjera

Instituciones
Extranjeras


Abstract



This article investigates solar energy storage due to the Jeffrey hybrid nanofluid flow containing gyrotactic microorganisms through a porous medium for parabolic trough solar collectors. The mechanism of thermophoresis and Brownian motion for the graphene and silver nanoparticles are also encountered in the suspension of water-based heat transfer fluid. The gyrotactic microorganisms have the ability to move in an upward direction in the nanofluid mixture, which enhances the nanoparticle stability and fluid mixing in the suspension. Mathematical modeling of the governing equations uses the conservation principles of mass, momentum, energy, concentration, and microorganism concentration. The non-similar variables are introduced to the dimensional governing equations to get the non-dimensional ordinary differential equations. The Cash and Carp method is implemented to solve the non-dimensional equations. The artificial neural network is also developed for the non-dimensional governing equations using the Levenberg Marquardt algorithm. Numerical findings corresponding to the diverse parameters influencing the nanofluid flow and heat transfer are presented in the graphs. The thermal profiles are observed to be enhanced with the escalation in the Darcy and Forchheimer parameters. And the Nusselt number enhances with the escalation in the Deborah number and retardation time parameter. Entropy generation reduces with an enhancement in Deborah number and retardation time parameter. Solar energy is the best renewable energy source. It can fulfill the energy requirements for the growth of industries and engineering applications.

Revista



Revista ISSN
Scientific Reports 2045-2322

Métricas Externas



PlumX Altmetric Dimensions

Muestra métricas de impacto externas asociadas a la publicación. Para mayor detalle:

Disciplinas de Investigación



WOS
Multidisciplinary Sciences
Scopus
Multidisciplinary
SciELO
Sin Disciplinas

Muestra la distribución de disciplinas para esta publicación.

Publicaciones WoS (Ediciones: ISSHP, ISTP, AHCI, SSCI, SCI), Scopus, SciELO Chile.

Colaboración Institucional



Muestra la distribución de colaboración, tanto nacional como extranjera, generada en esta publicación.


Autores - Afiliación



Ord. Autor Género Institución - País
1 Kumar, Anup - Birla Inst Technol & Sci Pilani - India
Birla Institute of Technology and Science, Pilani - India
2 Sharma, Bhupendra K. - Birla Inst Technol & Sci Pilani - India
Birla Institute of Technology and Science, Pilani - India
3 Almohsen, Bandar - King Saud Univ - Arabia Saudí
College of Sciences - Arabia Saudí
4 Perez, Laura M. - Universidad de Tarapacá - Chile
5 Urbanowicz, Kamil - West Pomeranian Univ Technol Szczecin - Polonia
West Pomeranian University of Technology, Szczecin - Polonia

Muestra la afiliación y género (detectado) para los co-autores de la publicación.

Financiamiento



Fuente
Fondo Nacional de Desarrollo Científico y Tecnológico
King Saud University
King Saud University, Riyadh, Saudi Arabia
Agencia Nacional de Investigación y Desarrollo
ANID through FONDECYT
Birla Institute of Technology and Science, Pilani

Muestra la fuente de financiamiento declarada en la publicación.

Agradecimientos



Agradecimiento
LMP acknowledges partial financial support from ANID through FONDECYT 1240985. The research is supported by Researchers Supporting Project number (RSP2025R158), King Saud University, Riyadh, Saudi Arabia.
LMP acknowledges partial financial support from ANID through FONDECYT 1240985. The research is supported by Researchers Supporting Project number (RSP2025R158), King Saud University, Riyadh, Saudi Arabia.
LMP acknowledges partial financial support from ANID through FONDECYT 1240985. The research is supported by Researchers Supporting Project number (RSP2025R158), King Saud University, Riyadh, Saudi Arabia.

Muestra la fuente de financiamiento declarada en la publicación.