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ANN‑based prediction of conjugate convective flow of micropolar nanofluids in inclined porous enclosures with Lorentz force

Research Abstract

Efficient heat transfer in inclined enclosures is critical for applications in thermal management, energy storage, and electronic cooling, yet the combined effects of micropolar nanofluids, porous media, and electromagnetic forces remain underexplored. This study investigates conjugate convective heat transfer in a porous inclined cavity filled with micropolar nanofluid under a tilted Lorentz force, where local thermal non-equilibrium is assumed between fluid and solid phases. The governing non linear equations are solved using the finite difference method (FDM), with adiabatic vertical walls and thermally conductive horizontal walls. To reduce computational cost, an artificial neural network (ANN) is trained on FDM-generated data to predict local Nusselt numbers. The results show that increasing the thickness of the solid wall from 0.05 to 0.3 reduces the maximum temperature by up to 84.28%, indicating improved thermal insulation characteristics. Additionally, higher solid volume fractions (up to 0.2) and stronger micropolar effects (vortex viscosity ratio up to 2.0) increase thermal resistance, resulting in a reduction in heat transfer of approximately 20%. Furthermore, enhancing the porosity of the medium from 0.1 to 0.9 leads to a 76.67% improvement in convective flow. This work advances the state of the art by coupling micropolar nanofluid dynamics, porous media, and tilted magnetic fields in inclined enclosures—an area not previously addressed with such detail. The integration of ANN with physics-based modeling offers a novel, high-fidelity, and computationally efficient framework for the optimization of complex thermal systems.

Research Department
Research Journal
Journal of the Brazilian Society of Mechanical Sciences and Engineering
Research Year
2025

Entropy generation due to MHD natural convection in a square enclosure with heater corners saturated porous medium using Cu/ water nanofluid containing insulated obstacle

Research Abstract

The significance of heat transfer and nanofluid flow in cavities with local heaters is investigated in the present study, crucial in numerous applications in engineering. The research focuses on the magnetohydrodynamic (MHD) with natural convection f low of Cu-water nanofluid inside a square cavity that includes a centrally positioned adiabatic block in square form. The enclosure features heated sections located proximate to all the corners (referred to as heated corners) with both the left and right wall sections being cooled. On the top and bottom walls, the remaining segments are adiabatic. This configuration sets the stage for exploring heat transfer dynamics and fluid behavior within the porous medium, offering insights into the thermal interactions within the cavity. The mathematical formulation of the problem is detailed in the subsequent section. Notably, it is clear that as heat source lengths increase, the local Nu number does as well (B) in all cases. The overall entropy generation is observed to diminish with a rise in the fraction of nanoparticle volume and the Rayleigh number. As the Hartmann number’s volume fraction rises, the average Nusselt number falls. Although the percentage of growth is higher for the rate of thermal performance, increasing the Darcy numbers improves the nanoparticle volume fraction. By raising the volume percentage of the nanoparticles, the total entropy creation is rising. The average Nu number falls with rising magnetic field strength

Research Department
Research Journal
Journal of the Brazilian Society of Mechanical Sciences and Engineering
Research Year
2025

Entropy generation for MHD natural bio-convection in porous cavity filled by a nano fluid containing gyrotactic microorganisms

Research Abstract

Thecurrent contributionemphasizesentropygenerationdue tobio-convection(Cu?TiO2)/H2O-modifiednano-liquid flowthroughtheL-shapedcavitywiththreeobstaclesconsideringtheaspectofgyrotacticmicroorganisms.Theactive sectionsofthebottomhorizontalandleftverticalwallsarepreservedcoolwhiletheotherportionsoftheporouscavityare insulated.ThefinitemethodisadoptedtosimulatethedimensionlessPDEsofthemodel.Theresultsdemonstratedhowthe influenceofthebio-convectionfactorsincreasesthedensityofmotilemicroorganisms.Ithasbeennotedthatthelocaland averageheat transmissionrateshaveincreasedwithhighervaluesof thelengthofcoldparts(heatsink), theverticaland horizontalwalls’ crest lengths, andnanoparticlevolume fraction. Largevalues of theRayleighnumber diminish the thermalperformancerate.Entropygeneration,localNusseltandSherwoodnumbers,anddensityofmotilemicroorganisms arealsoargued.

Research Department
Research Journal
Journal of the Brazilian Society of Mechanical Sciences and Engineering
Research Year
2025

Prediction of certain conjugate convective flow of a micropolar nano fluid in an inclined enclosure with the Lorentz force and porous medium by virtue of the artificial neural network

Research Abstract

Inclinedsquarecavitiesplayacritical role inengineeringapplications,partic ularlyinthermalmanagement,energystorageandelectroniccooling,whereinclinationangles in°uence convectiveheat transfer.This studyexamines conjugate convectiveheat transfer withinaninclinedsquarecavity¯lledwithmicropolarnano°uidsunderatiltedLorentzforce usinga two-phasenano°uidmodel.The systemincludes aheat-generatingporousmedium underthermalnonequilibrium, introducingcomplexdynamics.Factorssuchasthermalbuoy ancy,°uid{solidheattransfercoe±cientandmicropolar°uidpropertiesareanalyzedfortheir impact onheat transfer e±ciency.Methods:The studyuses the¯nitedi®erencemethod (FDM) to solvenonlinear equations governingconvective°owandheat transfer.Physica

Research Department
Research Journal
International Journal of Modern Physics B
Research Year
2025

Heat transfer analysis of Al₂O₃–Cu/water nanofluid in a C-shaped wavy cavity under inclined magnetic effects

Research Abstract

This study investigates the thermal dynamics of a C-shaped, wavy, porous cavity filled with Al₂O₃-Cu/H₂O hybrid nanofluids, influenced by an inclined magnetic field and a heat source/sink. The governing equations are non- dimensionalized and resolved using the finite difference method in a proprietary MATLAB solver. The study investigates the influence of numerous dimensionless parameters such as length of heat position(B = 0.2, 0.4, 0.8), heat source/sink (Q = 4, 0, 1), Porosity ( ∈ =0.1, 0.3, 0.9), Rayleigh number(Ra = 10, 100, 10000), Hartmann number(Ha = 0, 25, 50),length of a cavity (H = 0.5, 10, 100), length of ED/H (L2 = 0.2, 0.4, 0.6) and distance of AD/H (L1 = 0.2, 0.4, 0.6)are analyzed. The findings demonstrate that an elevated Rayleigh number augments convection, whilst increased porosity promotes heat transfer efficiency. The Al₂O₃-Cu/H₂O hybrid nanofluids markedly improve heat transfer owing to their exceptional thermal conductivity. The average Nusselt number validates the efficacy of hybrid nanofluids in enhancing thermal performance. The results indicate that hybrid nanofluids enhance heat transfer, while magnetic fields hinder convection, and the cavity shape in f luences flow patterns. By limiting convective flow, an increased Hartmann number leads to heat transport that is dominated by conduction. Additionally, the length of the heater has a direct influence on the generation of vortices and the enhancement of localized heat and heat transfer.

Research Department
Research Journal
International Journal of Thermofluids
Research Year
2025

Radiation and heat generation effect on MHDnaturalconvection in hybrid nanofluid-filled inclined wavy porous cavity incorporating a cross-shaped obstacle

Research Abstract

Purpose– Thispaperaimstoexplore,through a numerical study, buoyant convective phenomena in a porous cavity containing a hybrid nanofluid, taking into account the local thermal nonequilibrium (LTNE) approach. The cavity contains a solid block in the shape of a cross (þ). It will be helpful to develop and optimize the thermal systems with intricate geometries under LTNEconditions for a variety of applications

Research Department
Research Journal
International Journal of Numerical Methods for Heat &Fluid Flow
Research Year
2025

Artificial neural network valid at ion of MHD natural bioconvection in a square enclosure : entropic analysis and optimization

Research Abstract

Thisstudynumericallyinvestigatesinclinedmagneto-hydrodynamicnaturalconvectioninaporouscavityfilledwithnanofluid containinggyrotacticmicroorganisms.Thegoverningequationsarenondimensionalizedandsolvedusingthefinitevolume method. The simulations examine the impact of keyparameters suchas heat source lengthandposition, Peclet number, porosity,andheatgeneration/absorptiononflowpatterns, temperaturedistribution,concentrationprofiles,andmicroorganism rotation.Resultsindicatethatextendingtheheatsourcelengthenhancesconvectivecurrentsandheattransferefficiency,while optimizing the heat sourceposition reduces entropygeneration.Higher Peclet numbers amplify convective currents and microorganismdistribution complexity.Variations inporosityandheat generation/absorption significantly influence flow dynamics. Additionally, the artificial neural networkmodel reliably predicts themeanNusselt andSherwood numbers ( ) Nu Sh & ,demonstratingitseffectiveness for suchanalyses.Thesimulationresults reveal that increasingtheheat source lengthsignificantlyenhancesheat transfer, asevidencedbya15%increaseinthemeanNusseltnumber.

Research Authors
Noura Alsedais ,Mohamed Ahmed Mansour ,Abdelraheem Mahmoud Aly ,and Sara I. Abdelsalam
Research Department
Research Journal
Acta Mechanica Sinica
Research Year
2025
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