Computational examination of heat and mass transfer of nanofluid flow across an inclined cylinder with endothermic/exothermic chemical reaction

Case Studies in Thermal Engineering, Journal Year: 2024, Volume and Issue: 57, P. 104336 - 104336

Published: April 1, 2024

The consequence of thermal performance and mass distribution endothermic/exothermic chemical reaction pollutant concentration on the nanoliquid stream via cylinder/plate in presence permeable media is explored present study. advancement efficient waste disposal pollution prevention techniques might result from studies fluid flow dispersion contaminants cylinders plates. Further, TiO2 nanoparticle offers improved conductivity, helps wide range technological industrial applications. governing partial differential equations (PDEs) problem are modelled converted to ordinary (ODEs) utilizing similarity variables. resultant ODEs numerically solved using Runge Kutta Fehlberg's fourth-fifth order (RKF-45) scheme. influence various non-dimensional parameters velocity, thermal, profiles illustrated with a graphical representation. comparison between cylinder plate geometry also displayed graphs. novel outcomes show that augmentation parameter reduces profile endothermic case elevates exothermic case. Elevating local external source leads rise profile. It around 10%–12% Cf, 4%–6% Nu 8%–12% Sh observed than plate. transfer rate for values solid fraction activation energy. In all modes, performs better geometry.

Language: Английский

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Combining artificial intelligence and computational fluid dynamics for optimal design of laterally perforated finned heat sinks

Results in Engineering, Journal Year: 2024, Volume and Issue: 21, P. 102002 - 102002

Published: March 1, 2024

The efficient design of heat sinks is a severe challenge in thermo-fluid engineering. A creative and innovative way applying lateral perforations to parallel finned sinks. significance achieving an optimal for perforated (PFHSs) has inspired the present authors introduce novel hybrid designing approach that combines computational fluid dynamics (CFD), machine learning (ML), multi-objective optimization (MOO), multi-criteria decision-making (MCDM). variables considered include size (0.25<φ < 0.5) shape (square, circular, hexagonal) perforations, as well airflow Reynolds number (2000

Language: Английский

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Numerical and Experimental Study of Fluid Flow and Heat Transfer in Porous Media: A Review Article

Energies, Journal Year: 2025, Volume and Issue: 18(4), P. 976 - 976

Published: Feb. 18, 2025

Fluid flow and heat transfer in porous media have been extensively studied due to their importance numerous industrial environmental applications. This review provides a comprehensive analysis of numerical experimental approaches, presenting multiscale perspective that bridges molecular, pore, macroscopic levels. study emphasizes the understanding underlying principles governing these processes, as this knowledge is essential for optimizing innovating applications ranging from energy systems engineering. The synthesizes key theoretical frameworks, including Darcy’s law, Brinkman equation, volume-averaging methods, offering robust foundation interpreting complex interactions media. A novel aspect work integration insights address challenges such heterogeneity, anisotropy, scale effects, demonstrating complementary roles advancing field. Additionally, highlights emerging methodologies, advanced pore-scale modeling, lattice Boltzmann method, machine learning, transformative tools overcoming existing limitations exploring future directions. By identifying critical gaps proposing innovative solutions, article serves vital resource researchers practitioners, fostering interdisciplinary approaches paving way cutting-edge advancements fluid

Language: Английский

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Optimizing ternary hybrid nanofluids using neural networks, gene expression programming, and multi-objective particle swarm optimization: a computational intelligence strategy

Scientific Reports, Journal Year: 2025, Volume and Issue: 15(1)

Published: Jan. 15, 2025

The performance of nanofluids is largely determined by their thermophysical properties. Optimizing these properties can significantly enhance nanofluid performance. This study introduces a hybrid strategy based on computational intelligence to determine the optimal conditions for ternary nanofluids. goal minimize dynamic viscosity and maximize thermal conductivity varying volume fraction, temperature, nanomaterial mixing ratio. proposed integrates machine learning, multi-objective optimization, multi-criteria decision-making. Three learning techniques—GMDH-type neural network, gene expression programming, combinatorial algorithm—are applied model as functions input variables. Then, high-performing models provide foundation optimization using well-established particle swarm algorithm. Finally, decision-making technique TOPSIS employed identify most desirable points from Pareto front, various design scenarios. To validate strategy, composed graphene oxide (GO), iron (Fe₃O₄), titanium dioxide (TiO₂) was case study. results demonstrated that approach excelled in accurately modeling (R = 0.99964–0.99993). process revealed VFs span broad range across all ratios, while temperatures were consistently near maximum value (65 °C). outcomes indicated ratio consistent scenarios, with fraction serving key differentiating factor.

Language: Английский

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Entropy analysis of thermo-solutal stratification of nanofluid flow containing gyrotactic microorganisms over an inclined radiative stretching cylinder

Thermal Science and Engineering Progress, Journal Year: 2022, Volume and Issue: 34, P. 101379 - 101379

Published: June 20, 2022

Language: Английский

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Heat transfer enhancement of a PCM-porous metal based heat pipe evacuated tube solar collector: An experimental study

Solar Energy, Journal Year: 2023, Volume and Issue: 251, P. 106 - 118

Published: Jan. 19, 2023

Language: Английский

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Processes, models and the influencing factors for enhanced boiling heat transfer in porous structures

Renewable and Sustainable Energy Reviews, Journal Year: 2023, Volume and Issue: 192, P. 114244 - 114244

Published: Dec. 27, 2023

Language: Английский

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Develop the artificial neural network approach to predict thermal transport analysis of nanofluid inside a porous enclosure

Scientific Reports, Journal Year: 2023, Volume and Issue: 13(1)

Published: Nov. 29, 2023

Abstract This study explores the impacts of heat transportation on hybrid (Ag + MgO) nanofluid flow in a porous cavity using artificial neural networks (Bayesian regularization approach (BRT-ANN) technique). The considered this analysis is semicircular shape with heated and cooled wall. dynamics energy transmission are influenced by various features such as effect magnetize field, porosity volume fraction nanoparticles. To explore outcomes these thermal transport, BRT-ANN model developed. ANN trained dataset generated through numerical scheme. then used to predict transport characteristics for input parameters. accuracy simulation confirmed comparison predicted results obtained simulations. By maintaining corrugated wall uniformly heated, we inspected levels isotherms, streamlines transfer distribution. A graphical illustration highlights Hartmann Rayleigh numbers, permeability component material, drag force rate transport. According percentage analysis, nanofluids MgO/H 2 O) prominent enhance distribution traditional fluids. demonstrates potential ANNs predicting factors which can be useful designing optimizing systems.

Language: Английский

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Effect of filling height of metal foam on improving energy storage for a thermal storage tank

Applied Thermal Engineering, Journal Year: 2023, Volume and Issue: 229, P. 120584 - 120584

Published: April 15, 2023

Language: Английский

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Natural convection and entropy generation in a trapezoidal region with hybrid nanoliquid under magnetic field

International Journal of Numerical Methods for Heat &amp Fluid Flow, Journal Year: 2023, Volume and Issue: 34(2), P. 429 - 450

Published: July 18, 2023

Purpose This paper aims to study numerically the steady natural convective heat transfer of a hybrid nanosuspension (Ag-MgO/H2O) within partially heated/cooled trapezoidal region with linear temperature profiles at inclined walls under an effect uniform Lorentz force. investigation is useful for researchers studying in area cavity flows know features flow structures and nature nanofluid characteristics. In addition, detailed entropy generation analysis has been performed highlight possible regimes minimal rates. Design/methodology/approach The governing equations formulated using Oberbeck–Boussinesq approach single-phase nanoliquid model are transformed non-dimensional form by variables. obtained appropriate boundary conditions resolved finite difference technique. developed code validated comprehensively. Analysis wide range parameters, including Rayleigh number (Ra = 105), Prandtl (Pr 6.82), Hartmann (Ha 0–100), magnetic field inclination angle ( φ 0–?/2) nanoparticles volume fraction hnf 0 2%). Findings It shown that can be used manage energy transport performance. An inclusion without force influence allows forming more stable regime descending plume central zone, while such was clear fluid only moderate high numbers. Moreover, average overall decreased growth number, addition reducing this parameter Ha 30 50. Nusselt increased concentration low values intensity. Originality/value Governing written conservation laws dimensionless non-primitive variables have approach. created numerical verified applying grid independence test computational outcomes other researchers. comprehensive various key parameters performed.

Language: Английский

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