Analysis of nonlinear complex heat transfer MHD flow of Jeffrey nanofluid over an exponentially stretching sheet via three phase artificial intelligence and Machine Learning techniques

Chaos Solitons & Fractals, Год журнала: 2024, Номер 189, С. 115600 - 115600

Опубликована: Окт. 7, 2024

Язык: Английский

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Advanced intelligent computing ANN for momentum, thermal, and concentration boundary layers in plasma electro hydrodynamics burgers fluid

International Communications in Heat and Mass Transfer, Год журнала: 2024, Номер 159, С. 108195 - 108195

Опубликована: Окт. 23, 2024

Язык: Английский

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Intelligent Computing Technique to Analyze the Two-Phase Flow of Dusty Trihybrid Nanofluid with Cattaneo-Christov Heat Flux Model Using Levenberg-Marquardt Neural-Networks

Case Studies in Thermal Engineering, Год журнала: 2025, Номер unknown, С. 105891 - 105891

Опубликована: Фев. 1, 2025

Язык: Английский

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Analysis of thermal transport and wall stresses for MHD peristaltic motion of Reiner‐Philippoff fluid with viscous dissipation and mixed convection effects

ZAMM ‐ Journal of Applied Mathematics and Mechanics / Zeitschrift für Angewandte Mathematik und Mechanik, Год журнала: 2025, Номер 105(1)

Опубликована: Янв. 1, 2025

Abstract The present study examines the thermal characteristics and stresses at boundary for peristaltic motion of Reiner‐Philippoff fluid through a symmetric channel. (R‐P) model is widely recognized its ability to provide comprehensive representation unique properties exhibited by non‐Newtonian fluids. One notable aspect that initiates this nonlinear relationship between velocity gradient shear stress. Moreover, captures implicit connection deformation rate Additionally, R‐P exhibits distinct characteristics, acting as dilatant , exhibiting pseudoplastic behavior behaving Newtonian when . Governing equations are mathematically modeled under consideration mixed convection, viscous dissipation, magnetic field, Joule heating effects. Long wavelength small Reynolds number approximations used simplify system. To compute numerical solution simplified system, BVP4c technique employed via MATLAB. influences key parameters on flow physically visualized graphs. A detailed analysis heat transfer dilatant, pseudoplastic, fluids also provided. assessments wall presented tables. Outcomes reveal temperature profile decreases due parameter Bingham number. findings case indicate both enhanced Grashof Hartmann numbers lead an increase in profile. Tabular results improved developing values Brinkman numbers, while exhibit opposite behavior. decrease with greater Furthermore, more effective improving reducing compared

Язык: Английский

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Artificial neural network analysis of MHD Maxwell nanofluid flow over a porous medium in presence of Joule heating and nonlinear radiation effects

Chaos Solitons & Fractals, Год журнала: 2025, Номер 192, С. 116072 - 116072

Опубликована: Янв. 31, 2025

Язык: Английский

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Bayesian regularization-based intelligent computing for peristaltic propulsion of curvature-dependent channel walls

Physics of Fluids, Год журнала: 2025, Номер 37(2)

Опубликована: Фев. 1, 2025

This study investigates the numerical analysis of curvature-dependent symmetric channel walls filled with porous media, focusing on various flow characteristics using Artificial Neural Networks optimized Levenberg–Marquardt Backpropagation Scheme (ANNs-BLMS). The explores Electrically Conducting Peristaltic Propulsion Carreau–Yasuda Ternary Hybrid Nanofluids (ECPPCY-THNFs) propagating through sinusoidal wave trains within a curved conduit. To streamline analysis, governing equations have been simplified under specific assumptions lubrication theory. are solved Adam and three-stage Lobatto IIIa formula techniques to generate dataset spanning walls, covering four cases nine scenarios ECPPCY-THNFs. encompasses ECPPCY-THNFs, step size 0.02. As result, domain is divided into 131 grid points for velocity temperature profiles 71 rates heat transfer analysis. three parts: 10% training, testing, 80% validation. apply proposed methodology, constructed by varying Hartmann number, rate, Darcy curvature parameter, radiation parameter. Subsequently, an artificial intelligence-based algorithm employed derive solution expressions fields analyze dataset. results presented detailed tabular graphical illustrations. Heat performed model, findings validated multiple techniques, including error histograms, regression plots, mean square (MSE), time series autocorrelation, state transition. A comparative between two methods Intelligence (AI)-generated predictions also undertaken. obtained AI-based ANN-BLMS framework confirm reliability accuracy methodology in effectively solving demonstrate that parameter has considerable effect mechanical thermal aspects flow, therefore, it must be incorporated modeling flows channels. Additionally, rate 7.5 critical value, representing minimum required sustain fluid channel. When below this increase decrease profile. However, when exceeds profile shows opposite trend. Furthermore, ternary hybrid nanofluids show concave-up shapes (Θ) values greater than concave-down less 7.5. highest lowest velocities occur near center Θ>7.5 Θ<7.5, respectively. Moreover, coefficient determination values, used as performance indicators, found unity (1.000) ANN model. MSE histogram 2.8467 × 10−11 −3.05 10−7,

Язык: Английский

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Integration of artificial neural network computing for radially magnetized bioconvection peristaltic movement of Reiner-Philippoff nanofluid with porous medium

Journal of Molecular Liquids, Год журнала: 2024, Номер unknown, С. 126783 - 126783

Опубликована: Дек. 1, 2024

Язык: Английский

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Cross-coupling in hydrodynamic phase-field models for nonisothermal binary fluids

Chaos Solitons & Fractals, Год журнала: 2025, Номер 195, С. 116286 - 116286

Опубликована: Март 22, 2025

Язык: Английский

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Radiative heat and mass transfer significance through a permeable vertical plate with rotational effects: An artificial approach using the Levenberg–Marquardt algorithm

AIP Advances, Год журнала: 2025, Номер 15(4)

Опубликована: Апрель 1, 2025

We examine a heat-absorbing viscous fluid’s electrically conducting boundary layer flow over semi-infinite permeable plate in porous medium inclined at an angle α. Nonlinear partial differential equations are solved using perturbation methods, and graphical analysis is used to determine how parameters impact concentration, temperature, velocity profiles. Buoyancy forces increase fluid with the increased Grashof number. However, presence of magnetic (Lorentz) rotational (Coriolis) effects introduces resistance, leading reduction velocity. A direct relationship observed between number skin friction, while radiation parameter inversely affects Nusselt An Schmidt lowers Sherwood also investigate rotation on unsteady magnetohydrodynamic slip Artificial Neural Network (ANN) model employing Levenberg–Marquardt Backpropagation. The ANN accurately predicts dynamics heat transfer numerical simulation data. Model accuracy validated through mean squared error graphs, regression analysis, histograms, demonstrating reliable predictions under varying conditions.

Язык: Английский

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Thermal transport and irreversibility analysis for radially magnetized Carreau–Yasuda nanofluids flow over polished surfaces

Modern Physics Letters B, Год журнала: 2025, Номер unknown

Опубликована: Апрель 14, 2025

A major challenge in modern industry is the need for efficient heat transfer fluids, as conventional fluids often do not provide necessary efficiency heating and cooling processes. Nanofluids, seen future of are developed by dispersing nanoparticles into base fluids. Owing to their unique dynamic thermophysical properties, these innovative nanofluids have a broad spectrum applications nanotechnology advanced systems. Based on nanofluids, flow composed graphene suspended lubricant oil with studied here. Flow induced curved stretching sheet. The surface sheet considered be polished uniformly, which hence facilitates velocity slip. novelty this study lies utilizing rheological properties dispersed oil-based fluid, empirically investigated Bakak et al. (2021). Their findings suggest that nanofluid exhibits non-Newtonian behavior, experimental data closely aligning Carreau–Yasuda model. radially varying magnetic field influences generating Lorentz force Ohmic heating. In view experimentally reported results, depicted using Furthermore, configuration influenced thermal radiation, source, viscous dissipation, convective at boundary. Irreversibility analysis carried out propose ways energy optimization. Boundary layer approximations utilized model partial differential equations (PDEs) governing system. By applying non-similarity transformation, original PDEs converted dimensionless nonlinear PDEs. local approach, truncated second order, reducing them ordinary (ODEs) can more easily solved. resulting system tackled through BVP4c algorithm MATLAB. Influences pertinent parameters profile, drag force, isotherms, nanofluid’s temperature, streamlines, entropy generation number, rates, Bejan number analyzed graphs tables. Findings indicate temperature distribution improves higher values Biot Weissenberg number. Additionally, decreases increasing Also, it noted velocity. demonstrates direct relationship profile. magnitude coefficient curvature parameter volume fraction nanoparticles. Heat rises elevated parameter, Eckert source radiation but an increase

Язык: Английский

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