Development of machine learning algorithm for assessment of heat transfer of ternary hybrid nanofluid flow towards three different geometries: Case of artificial neural network

Heliyon, Год журнала: 2023, Номер 9(11), С. e21453 - e21453

Опубликована: Ноя. 1, 2023

The focus of this paper revolves around the examination flow ternary hybrid nanofluid, specifically Al2O3-Cu-CNT/water mixture, with buoyancy effect, across three distinct geometries: a wedge, flat plate, and cone. study takes into account presence quadratic thermal radiation heat source/sink non-uniform nature. To develop model, Cattaneo-Christov theory is utilized. equations governing are solved by applying similarity transformations employing "bvp4c function in MATLAB" for numerical analysis solution. Conventional methods conducting parametric studies often face challenges producing significant conclusions owing to inherent complex form model method involved. address aforementioned issue, explores potential machine learning foresee conduct characterized multiple interconnected parameters. By utilizing simulated data, an artificial neural network trained using Levenberg-Marquardt algorithm learn comprehend underlying patterns. Subsequently, employed estimate Nusselt number on surfaces all geometries. This approach offers promising alternative traditional studies, enabling more precise predictions insights behavior systems. highest THNF over mean squared error (MSE) values ANN algorithm, analyzed cases, range from 0 0.03972. findings contribute improved understanding characteristics dynamics nanofluid various geometries, assisting design optimization transfer systems involving such fluids.

Язык: Английский

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Importance of thermophoretic particles deposition in ternary hybrid nanofluid with local thermal non-equilibrium conditions: Hamilton–Crosser and Yamada–Ota models

Case Studies in Thermal Engineering, Год журнала: 2024, Номер 56, С. 104229 - 104229

Опубликована: Март 14, 2024

This article exhibits a brief study of magneto ternary hybrid nanofluid flow with thermophoretic particle deposition and porous medium based on the extended version model, known as Yamada-Ota Hamilton Crosser models. Thermophoretic deposition, which is important in both aero-solution electrical engineering, one most fundamental methods for transferring small particles across heat gradient. suggested model's goal to evaluate how well Hamilton-Crosser Yamada-Ota, two trihybrid models, perform. Advanced transfer systems, particular creation effective cooling heating technologies, may benefit from this research. Researchers can develop more efficient exchangers, boost thermal management electronic devices, increase energy efficiency industrial processes by better understanding behave complicated systems under various conditions. By using required similarity variables, MATLAB solver bvp4c package handles system ODEs acquired leading PDEs arrive at numerical solution. The relevant parameters' effects fields have been graphically explained. results show that when inter-phase parameter value grows, profile rate decrease liquid phase. With regard mass effectiveness, model performs than model.

Язык: Английский

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Heat and mass exchanger analysis for Ree-Eyring hybrid nanofluid through a stretching sheet utilizing the homotopy perturbation method

Case Studies in Thermal Engineering, Год журнала: 2024, Номер 54, С. 104014 - 104014

Опубликована: Янв. 11, 2024

An investigation is being carried out to describe the flow of a Ree-Eyring hybrid nanofluid by stretch flow. SiO2 and GO are examined for use as nanoparticles in accumulation with carboxymethyl cellulose (CMC) water at low concentrations. A concentration between 0.0 0.4 % suggested base fluid (CMC− water). The model equations firstly converted into ordinary differential through suitable alteration. Homotopy Perturbation Method (HPM) R–K method were applied governing (ODEs). produced results identified numerical technique. Both these methods approval demonstrate that our approach achieves an acceptable level accuracy. obtained data behaviours velocity, temperature, about other physical factors. Multiple graphs illustrating conclusions significance shown thoroughly analyzed. most important findings from this research show stretching sheet has role determining depth boundary layer. By raising Weissenberg number, thickness layer will be enhanced, which lead augmentation velocity non-Newtonian fluid. Moreover, Prandtl number was second crucial variable explored, it follows enhancing effect lessening thermal last parameter Schmidt increasing caused significant reduction mass

Язык: Английский

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Entropy analysis of MHD hybrid nanoparticles with OHAM considering viscous dissipation and thermal radiation

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Янв. 11, 2024

Abstract This research explores the 3-D flow characteristics, entropy generation and heat transmission behavior of nanofluids consisting copper titanium in water as they across a bidirectional apparent, while considering influence magneto-hydrodynamics. The thermophysical properties are taken advantage utilizing Tiwari Das demonstrate. concept boundary layer has facilitated comprehension physical ideas derived from it. By applying requisite transformations, connected intricate sets partial differential equation have been converted into ordinary equation. modified model is calculated employing widely recognized technique known OHAM by using Mathematica program BVPh2.0 Software. For different dimensionless parameters computational graphical investigations performed. It notice that fluid change, exhibit distinct responses comparison to temperature, velocity profiles generation. results show profile rise with greater estimates magnetic parameter rate formation. Furthermore, thermal become less significant Eckert Prandtl numbers increase.

Язык: Английский

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Exploring nanoparticle dynamics in binary chemical reactions within magnetized porous media: a computational analysis

Scientific Reports, Год журнала: 2024, Номер 14(1)

Опубликована: Окт. 26, 2024

Artificial Neural Networks are incredibly efficient at handling complicated and nonlinear mathematical problems, making them very useful for tackling these challenges. neural networks offer a special computational architecture that is extremely valuable in disciplines like biotechnology, biological computing, fluid dynamics. The present work investigates the applicability of back-propagation artificial conjunction with Levenberg-Marquardt algorithm evaluating heat transmission hybrid nanofluids. This focuses on analysis MgO + GO/EG nanofluid's steady mixed convection flow over an exponentially stretched sheet, considering multiple slip boundary conditions, thermal conductivity, generation, radiation. A system ordinary differential equations produced from basic associated partial by performing proper exponential similarities modifications. For generating benchmark datasets, resulting processed employing bvp4c method. Considering datasets set aside training (70%), testing (15%), validation algorithm, which employs networks, implemented. accuracy suggested strategy problems verified utilizing mean squared error, error histograms, regression analysis, all used to evaluate methodology. Outstanding agreement seen when ANN outputs compared numerical results. properties, including temperature, velocity, concentration profiles, shown graphically numerically. practical purposes, it therefore essential analyze transfer nanofluids extending shrinking surfaces under source scenarios. Hybrid nanofluid have wide range industrial applications, such as medication delivery, manufacturing, microelectronics, nuclear plant cooling, marine engineering.

Язык: Английский

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

Scientific Reports, Год журнала: 2023, Номер 13(1)

Опубликована: Ноя. 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.

Язык: Английский

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Chemically radioactive unsteady nonlinear convective couple stress Casson hybrid nanofluid flow over a gyrating sphere

Journal of Thermal Analysis and Calorimetry, Год журнала: 2023, Номер 148(22), С. 12583 - 12595

Опубликована: Окт. 18, 2023

Язык: Английский

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Entropy generation optimization of cilia regulated MHD ternary hybrid Jeffery nanofluid with Arrhenius activation energy and induced magnetic field

Scientific Reports, Год журнала: 2023, Номер 13(1)

Опубликована: Сен. 2, 2023

This study deals with the entropy generation analysis of synthetic cilia using a ternary hybrid nanofluid (Al-Cu-Fe2O3/Blood) flow through an inclined channel. The objective current is to investigate effects optimization, heat, and mass transfer on passing channel in proximity induced magnetic field. novelty present studying combined effect viscous dissipation, thermophoresis, Brownian motion, exponential heat sink/source, porous medium, endothermic-exothermic chemical reactions, activation energy field examined. governing partial differential equations (PDEs) are transformed into ordinary (ODEs) appropriate transformations. Applying low Reynolds number long-wavelength approximation, resultant ODEs numerically solved shooting technique via BVP5C MATLAB. velocity, temperature, concentration, magnetism profiles visually discussed graphically analyzed for various fluid parameters. Graphical physical interest quantities like rate, skin friction coefficient also discussed. improves enhancing values number, solutal Grashof sink/source parameter, Brinkman Prandtl reaction parameter while reverse noticed parameter. findings this can be applied enhance efficiency biomedical devices, optimizing cooling systems, designing efficient conversion processes, spanning from renewable technologies aerospace propulsion systems.

Язык: Английский

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Unsteady mix convectional stagnation point flow of nanofluid over a movable electro-magnetohydrodynamics Riga plate numerical approach

Scientific Reports, Год журнала: 2023, Номер 13(1)

Опубликована: Июль 6, 2023

Abstract The flow at a time-independent separable stagnation point on Riga plate under thermal radiation and electro-magnetohydrodynamic settings is examined in this research. Two distinct base fluids-H 2 O C H 6 TiO nanostructures develop the nanocomposites. problem incorporates equations of motion energy along with unique model for viscosity conductivity. Similarity components are then used to reduce these calculations. Runge Kutta (RK-4) function yields simulation result, which displayed graphical tabular form. For both involved fluid theories, nanofluids profiles relating relevant aspects computed analyzed. According findings research, heat exchange rate significantly higher than model. As volume percentage nanoparticles rises, velocity field degrades while temperature distribution improves. Moreover, greater acceleration parameters, / has highest coefficient whereas skin friction coefficient. key observation that nanofluid little performance nanofluid.

Язык: Английский

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Significant statistical model of heat transfer rate in radiative Carreau tri-hybrid nanofluid with entropy analysis using response surface methodology used in solar aircraft

Renewable Energy, Год журнала: 2024, Номер unknown, С. 121521 - 121521

Опубликована: Окт. 1, 2024

Язык: Английский

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