Effect Of Heat Generation Research Articles

Mathematical model of second-grade Casson fluid flow with Soret and Dufour impact over Riga sheet

We are examining a mathematical model of second-grade Casson fluid flow over a Riga surface. This analysis takes into account the effects of heat generation on a second-grade Casson fluid. Additionally, we have discussed the impacts of Soret and Dufour in the presence of thermal radiation. The study also includes an analysis of the influences of thermal and concentration slip. By considering these factors in the fluid flow, we have constructed a set of partial differential equations. Furthermore, these differential equations have been transformed into dimensionless ordinary differential equations. We have presented the influences of relevant parameters through tables and graphs. Velocity curve reveals declining behavior due to larger values of magnetic field factor. A high magnetic field coefficient means a strong magnetic field. As a result, the force acting on the charged particle increases, causing it to slow down or change direction. This change in force can cause the particle’s velocity to decrease.

Utilization of variable thermal conductivity and diffusion coefficient on non-Newtonian Prandtl model with modified heat and mass fluxes

PurposeThis study aims to analyze the Prandtl fluid flow in the presence of better mass diffusion and heat conduction models. By taking into account a linearly bidirectional stretchable sheet, flow is produced. Heat generation effect, thermal radiation, variable thermal conductivity, variable diffusion coefficient and Cattaneo–Christov double diffusion models are used to evaluate thermal and concentration diffusions.Design/methodology/approachThe governing partial differential equations (PDEs) have been made simpler using a boundary layer method. Strong nonlinear ordinary differential equations (ODEs) relate to appropriate non-dimensional similarity variables. The optimal homotopy analysis technique is used to develop solution.FindingsGraphs analyze the impact of many relevant factors on temperature and concentration. The physical parameters, such as mass and heat transfer rates at the wall and surface drag coefficients, are also displayed and explained.Originality/valueThe reported work discusses the contribution of generalized flux models to note their impact on heat and mass transport.

Thermal scrutinization of a triangular porous fin induced by linear and nonlinear temperature-dependent heat generation and magnetic field effect: the case of Darcy model

Thermal scrutinization of a triangular porous fin induced by linear and nonlinear temperature-dependent heat generation and magnetic field effect: the case of Darcy model

Heat generation and melting heat transfer effects on MHD flow of Carreau fluid in a porous medium

AbstractWe consider heat and mass transfer analysis of magnetohydrodynamic (MHD) Carreau fluid flow along a stretching sheet in a permeable medium with impacts of melting condition, heat generation, double diffusion, and variable thermal conductivity. The novelty of the present work is to study the effects of melting heat transfer and heat generation on MHD flow of Carreau fluid along a stretched sheet in a porous medium with influence of Dufour and Soret effects, and variable thermal conductivity. Similarity transformations procedure is used which transform the partial differential equations (PDEs) of fluid flow model into nonlinear dimensionless ordinary differential equations (ODEs). We obtained numerical solutions of ODEs and the effects of assorted governing parameters are investigated. The results showed that boosting melting parameter increases velocity and concentration fields and reduces temperature profile. Enhancing heat source parameter increases temperature profile, concentration profile observing decline for modified Dufour parameter, Schmidt number, and Soret number, and velocity of the fluid decline for magnetic and porosity parameters. Impact of governing parameters on physical quantities comprising Nusselt number, skin friction, and Sherwood number is evaluated numerically. The accuracy of our results are established in comparison with previous research for skin friction coefficient and Nusselt number.

Second-grade fluid with carbon nanotubes flowing over an elongated curve surface possessing thermal radiation and internal heat generation effects

Second-grade fluid with carbon nanotubes flowing over an elongated curve surface possessing thermal radiation and internal heat generation effects

Effects of Heat Generation and Chemical Reaction on Time-Dependent MHD Natural Convective Transport Past in a Vertical Perforated Sheet

Effects of Heat Generation and Chemical Reaction on Time-Dependent MHD Natural Convective Transport Past in a Vertical Perforated Sheet

Application of Constant Proportional Caputo Fractional Derivative to Thermodiffusion Flow of MHD Radiative Maxwell Fluid under Slip Effect over a Moving Flat Surface with Heat and Mass Diffusion

Thermal diffusion is a phenomenon where the concentration gradient or diffusive flux is created due to the temperature gradient. Thermal diffusion is induced because of the higher temperature and uneven distribution of the mixture. Formally, thermal diffusion is called the Soret effect, and it is a crucial factor in a number of natural occurrences like the separation of isotopes technique of purification. In this research paper, Maxwell fluid’s flow in the vicinage of a flat plate is discussed by considering the effect of the thermodiffusion subject to the first-order slip at the boundary with the application of a constant proportional Caputo (CPC) fractional derivative. The effect of heat generation and radiation is also taken into consideration, as well as the effect of a magnetic field of constant magnitude. The generalized heat and mass fluxes are considered, and this generalization of heat and mass fluxes is done by utilizing the CPC fractional derivative. After converting the current model’s governing equations into a dimensionless form, the temperature, concentration, and velocity fields’ analytical solutions are found. By drawing graphs of the temperature, concentration, and velocity fields for the parametric modifications, the results are graphically illustrated. It becomes clear from the results discussion that the outcomes produced by the constant proportional derivative are more decaying than those obtained with the classical differential operator of order one.

Heat transfer analysis of single-walled carbon nanotubes in Ellis's fluid model: Comparative study of uniform and non-uniform channels

BackgroundThe essential features of nanoparticles in nanofluids play a vital role in nanotechnology. The nanosized particles of carbon are known as carbon nanotubes (CNTs). The properties of CNT like thermal and electrical conductivity, lightweight, flexibility, and mechanical strength support its applications in the medical field i.e., diagnostic and therapeutic agents (drugs, antibodies, biosensors, vaccines etc.). These are not only excellent vehicles for drug delivery and gene therapies but also useful in biosensor diagnostic, enantiomer separation of chiral drugs, tissue regeneration, extraction, and analysis of pollutants and drugs. ObjectiveThe focus of this research work is to open the essential features of peristaltic transport of Ellis nanofluid through uniform and non-uniform channels with suspension of single-walled carbon nanotubes (SWCNT). The consideration of blood flow with SWCNT under the effects of heat generation and electroosmosis is one of the key factors of this investigation. MethodThe complexity of the system is reduced with the implementation of the concepts of longer wavelength and lower Reynolds number. The governing two-dimensional equations are simplified by introducing dimensionless variables and parameters. The mathematical tool “MATHEMATICA 13.3” is used to compute the exact solution and graphical demonstration of velocity, temperature, heat transfer rate, and streamlines. Computational resultsIt is noticed that velocity, temperature, and heat transfer rate are prominent in non-uniform channels as compared to uniform channels. Similarly, the size and number of boluses during the trapping phenomenon increase or decrease quickly in non-uniform channels. The volumetric addition of SWCNT diminishes the velocity and temperature while the heat transfer rate is enhanced in both channels but in the nonuniform channel effects are more prominent. ApplicationsThis study explores the applications of SWCNT in medical fields like angiography, angioplasty, and cancer therapy. NoveltyThe present study is new and has never been addressed before.

Machine learning based analysis of heat transfer in tangent hyperbolic fluid at heat generating magnetized surface

An artificial intelligence-based study is conducted to examine the heat transfer in the tangent hyperbolic fluid using a stretchable magnetized surface. To be more specific, heat and mass transfer are considered in the flow regime of tangent hyperbolic fluid. The magnetic field is applied externally. The heat generation, velocity, and thermal slip effects are considered. The flow is formulated in terms of coupled non-linear PDEs. Lie groups of transformations are constructed to reduce the order of PDEs. The reduced equations are solved by using the shooting method. The impact of the Weissenberg number, power law index, Prandtl number, and heat generation parameter is evaluated on the heat transfer coefficient by using artificial intelligence. 88 samples are divided at random into training 62 (70 %), validation 13 (15 %), and testing 13 (15 %). The hidden layer contains 10 neurons. The Levenberg-Marquadt backpropagation algorithm is used to train the model. The developed model is evaluated by mean square error and regression analysis. According to ANN anticipated values, the heat transfer coefficient shows decreasing trends towards higher values of Weissenberg number, power law index, and heat generation parameter. The tangent hyperbolic fluid temperature admits an increase for heat generation and magnetic field parameter while the opposite is the case for thermal slip parameter.

Numerical Investigation of Nanofluid as a Coolant in a Prismatic Battery for Thermal Management Systems

Abstract This study delves into the realm of numerical investigation of the heat transfer performance of nanofluids as coolants for prismatic batteries. Nanofluids are being employed in battery cooling systems to enhance overall thermal management and ensure the safe operation of batteries, particularly in situations involving high heat generation. In this study, different types of nanofluids were used along with a base fluid of ethylene glycol–water (EG–water 50%). The energy equations consider the effects of viscous dissipation and heat generation. The model generates a set of nonlinear partial differential equations, which can be transformed into ordinary differential equations (ODEs) using appropriate similarity variables. These ODEs are then solved numerically by employing the Runge–Kutta–Fehlberg method along with the shooting method to obtain solutions. The simulations in both 2D and 3D showcase the results for various parameters pertaining to thermal and velocity fields, heat transfer rate, and drag force. The findings reveal that heat generation leads to a staggering increase in temperature of 78.22%. However, using aluminum nanoparticles (NPs) as opposed to copper nanoparticles quickly reduced the battery’s maximum temperature by 9.31%. The exceptional heat generation strengths of CuO–EG and Al2O3–EG nanofluids also resulted in a significant increase in their heat transfer rates of around 40.42% and 42.13%, respectively. Additionally, the aluminum NPs exhibited a more rapid heat transfer rate of 4.06% when compared to the copper nanoparticles. This research contributes to the development of improved cooling strategies for prismatic battery applications, ultimately paving the way for enhanced battery performance, an extended lifespan, and improved safety in a wide range of industries and electric vehicles.

Neural networking-based analysis of heat transfer in MHD thermally slip Carreau fluid flow with heat generation

The formulation of heat transfer in non-Newtonian fluid models remains a topic of great interest for researchers. The ultimate flow differential equations in this direction are non-linear and hence difficult to solve analytically. Therefore, we offer state of the art determination of film effectiveness (heat transfer coefficient) by using artificial intelligence (AI). To be more specific, the Carreau fluid model is formulated at a flat surface along with thermal slip, heat generation, velocity slip, chemical reaction, and magnetohydrodynamics (MHD) effects. The developed equations are reduced by the application of the Lie symmetry approach and solved by the shooting method. The artificial neural networking model is built by using 132 sample values of the Nusselt number (NN) as an output. Porosity parameter, Prandtl number, magnetic field parameter, and heat production parameter are all inputs. 92 (70 %) is designated for training, whereas 20 (15 %) is designated for validation and testing. The Levenberg-Marquardt algorithm is used to train the neural network. The constructed artificial neural networking (ANN) is best to predict the NN at a flat surface. It is observed that for large Prandtl numbers, the magnitude of the Nusselt number is greater for porous surface, but the converse is true for magnetic field parameter.

LOCAL NON-SIMILAR SOLUTIONS OF MAGNETOHYDRODYNAMIC CASSON NANOFLUID FLOW OVER A NON-LINEAR INCLINED SURFACE WITH THERMAL RADIATION AND HEAT GENERATION EFFECTS: A UTILIZATION OF UP TO THIRD TRUNCATION

The current research aims to investigate the influences of thermal radiation, heat generation, and chemical reaction on the magnetohydrodynamic (MHD) Casson fluid flow model over a non-linear inclined surface. The Buongiorno model of the thermal efficiency of fluid flows in the existence of Brownian motion and thermophoresis features served as the foundation of employed non-similar modeling. The present article uses the local non-similarity assumption to solve the problem up to the third degree of truncation. The pseudo similarity parameter, stream function, and modified streamwise coordinate all satisfy the continuity equation in the same way, which transforms the energy, momentum, and mass equations into a non-similar dimensionless boundary layer (BL) problem. Here, the non-similar equations up to third level of truncation are generated in order to compare the numerical results produced by the different iterations. The built-in MATLAB function bvp4c is used to discover numerical values to these equations. In terms of energy, velocity, and mass configuration, the effect of particular physical factors are stated; as the inclination parameter and magnetic parameter increase, the velocity outline decreases. The velocity profile improves when a rise in the Casson fluid factor is observed. As heat generation and absorption increases, the energy profile rises. The growth of the thermophoresis factor and chemical reaction parameter reduces the concentration profile. Mass diffusion portrays increases as the Brownian motion factor rises. Moreover, to compare the answers with various levels of truncation, the relative error was also estimated. The present work is finally validated by comparison with previously published articles for a reduced Nusselt number and Sherwood number.

THERMAL ANALYSIS OF BI-DIRECTIONAL FUNCTIONALLY GRADED PLATES SUBJECTED TO HEAT GENERATION

The two-dimensional steady-state heat transfer problem is analyzed under the most general boundary conditions in a heterogeneous environment. It is assumed that the internal heat generation varies arbitrarily in two directions, while the thermal conductivity coefficient of the material is bi-directly (thickness-length) graded with the Mori-Tanaka model. The linear inhomogeneous partial differential equations produced under these conditions may not be solved by conventional methods. The governing equation of the system is numerically solved with high accuracy using the 2D pseudospectral Chebyshev method. Benchmark problems are used to check the accuracy of the method. It has been observed that the effect of volumetric heat generation on the temperature distribution is more than the heat transmission coefficient. Besides, this method is simple and effective and can be easily applied to such problems.

Calibrating a Heat Transfer Model for Baled Switchgrass Using Heat Generation

HighlightsHeat and mass transfer in baled switchgrass was modeled based on thermal conductivity and internal heat generation.Model calibration was performed through a 60-day storage evaluation of baled switchgrass in an environmental chamber.Empirical models of heat generation and DML were developed based on thermal conductivity and aerobic respiration.Model validation was performed based on an energy balance and the aerobic respiration rate of switchgrass.Abstract. This study characterizes heat transfer within baled switchgrass through the development of a two-dimensional heat conduction model and an exponential drying approach to predict moisture content. The model was simulated using the finite difference method while accounting for the effect of internal heat generation to improve prediction accuracy. Model calibration was performed using rectangular bales of switchgrass (102 x 46 x 36 cm) stored in a controlled environmental chamber for 60 days at a fixed temperature and relative humidity. The heat and mass transfer model was implemented as an inverse model to empirically estimate heat generation and dry matter loss (DML). Internal heat generation and dry matter losses were also assessed using previously published models describing the aerobic respiration rate of switchgrass. Both heat generation models were in close agreement at a nominal moisture content of 10% w.b. (R2 = 0.9542) but deviated at nominal moisture contents of 20% to 40% w.b. (R2 < 0.7543). DML simulated using the numerical model closely agreed with the DML measured in the storage evaluation (R2 > 0.9060), indicating sufficient DML estimates through the conduction model and exponential drying approach. DML simulated through the published aerobic respiration model deviated to a greater extent, particularly at the highest moisture treatment (R2 = 0.4340), indicating an insufficient consideration of the various biochemical processes occurring at elevated levels of moisture and density. The results of this study provide a framework for the development of post-harvest quality models to optimize the storage, drying, and bioconversion of baled biomass feedstocks. Keywords: Bales, Heat and mass transfer, Heat transfer model, Storage losses, Switchgrass.

An artificial neural network analysis of the thermal distribution of a fractional-order radial porous fin influenced by an inclined magnetic field

<abstract><p>Fins and radial fins are essential elements in engineering applications, serving as critical components to optimize heat transfer and improve thermal management in a wide range of sectors. The thermal distribution within a radial porous fin was investigated in this study under steady-state conditions, with an emphasis on the impact of different factors. The introduction of an inclined magnetic field was investigated to assess the effects of convection and internal heat generation on the thermal behavior of the fin. The dimensionless form of the governing temperature equation was utilized to facilitate analysis. Numerical solutions were obtained through the implementation of the Hybrid Cuckoo Search Algorithm-based Artificial Neural Network (HCS-ANN). The Hartmann number (M) and the Convection-Conduction parameter (Nc) were utilized in the evaluation of heat transfer efficiency. Enhanced efficiency, as evidenced by decreased temperature and enhanced heat removal, was correlated with higher values of these parameters. Residual errors for both M and Nc were contained within a specified range of $ 10^{-6} $ to $ 10^{-14} $, thereby offering a quantitative assessment of the model's accuracy. As a crucial instrument for assessing the performance and dependability of predictive models, the residual analysis highlighted the impact of fractional orders on temperature fluctuations. As the Hartmann number increased, the rate of heat transfer accelerated, demonstrating the magnetic field's inhibitory effect on convection heat transport, according to the study. The complex relationship among Nc, fractional order (BETA), and temperature was underscored, which motivated additional research to improve our comprehension of the intricate physical mechanisms involved. This study enhanced the overall understanding of thermal dynamics in radial porous fins, providing significant implications for a wide array of applications, including aerospace systems and heat exchangers.</p></abstract>

Artificial intelligence (AI) based neural networks for a magnetized surface subject to tangent hyperbolic fluid flow with multiple slip boundary conditions

<abstract> <p>In this paper, the Levenberg-Marquardt backpropagation scheme is used to develop a neural network model for the examination of the fluid flow on a magnetized flat surface with slip boundaries. The tangent hyperbolic fluid is considered along with heat generation, velocity, and thermal slip effects at the surface. The problem is modelled in terms of a non-linear differential system and Lie symmetry is used to get the scaling group of transformation. The order reduction of differential equations is done by using Lie transformation. The reduced system is solved by the shooting method. The surface quantity, namely skin friction, is evaluated at the surface for the absence and presence of an externally applied magnetic field. A total of 88 sample values are estimated for developing an artificial neural network model to predict skin friction coefficient (SFC). Weissenberg number, magnetic field parameter, and power law index are considered three inputs in the first layer, while 10 neurons are taken in the hidden layer. 62 (70%), 13 (15%), and 13 (15%) samples are used for training, validation, and testing, respectively. The Levenberg-Marquardt backpropagation is used to train the network by entertaining the random 62 sample values. Both mean square error and regression analysis are used to check the performance of the developed neural networking model. The SFC is noticed to be high at a magnetized surface for power law index and Weissenberg number.</p> </abstract>

Managing heat transfer effectiveness in a Darcy medium with a vertically non-linear stretching surface through the flow of an electrically conductive non-Newtonian nanofluid

<abstract><p>This study encapsulated the research methodology utilized in the flow behaviors of Williamson nanofluid and analyzed the associated mass heat transfer. The study concentrated on examining the magnetohydrodynamic behavior of nanofluids in the presence of heat generation effects and the inclusion of dissipative energy on a vertical nonlinear stretching surface submerged within a Darcy porous medium. The rationale for including variable viscosity and variable conductivity in this research was to precisely evaluate the mechanisms of heat and mass transfer, particularly with regard to the fluctuations in fluid properties. The objective was to enhance the understanding of how these varying properties impact the overall heat and mass transfer processes. The initial formulation of the phenomenon, initially presented as partial differential equations, was transformed into ordinary differential equations by employing appropriate dimensionless variables. The ultimate streamlined version of the model was then numerically solved utilizing the shooting method. By employing the numerical shooting method, we portrayed nanofluid patterns in velocity, temperature, and concentration fields, alongside essential parameters such as skin friction coefficient, Sherwood number, and Nusselt number. The significant key findings highlighted that both the porous parameter and the magnetic number increasingly affected temperature and concentration distributions. Additionally, increasing the thermophoresis parameter resulted in higher concentration and corresponding temperature levels. Graphical presentation and physical explanations were used for analysis, and the study's outcomes were compared to existing literature, affirming a strong agreement that validated the solutions.</p></abstract>

Numerical treatment of the radiated and dissipative power-law nanofluid flow past a nonlinear stretched sheet with non-uniform heat generation

The main aim of this paper is to investigate the effect of non-uniform heat generation and viscous dissipation on the boundary layer flow of a power-law nanofluid over a nonlinear stretching sheet. Within the thermal domain, the analysis considers both thermal radiation and variable thermal conductivity. Through the use of similarity transformations, the governing boundary layer equations are transformed into a system of ODEs. The spectral collocation method (SCM) with shifted Vieta-Lucas polynomials (VLPs) is implemented to give an approximate expression for the derivatives and then use it to numerically solve the proposed system of equations. By employing this technique, the system of ODEs is converted into a system of nonlinear algebraic equations. The dimensionless temperature, concentration, and velocity are graphically presented and analyzed for various values of the relevant governing parameters. Through the presented graphical solutions, we can see that the main outcomes indicate that an increase in the power law index, thermal conductivity parameter, and radiation parameter leads to a noticeable decrease in the local Nusselt number, with reductions of around 0.05 percent, 0.23 percent, and 0.11 percent, respectively. In contrast, the Prandtl parameter demonstrates an opposing effect, elevating the local Nusselt number by about 0.1 percent. We validated the accuracy of the numerical solutions by comparing them in some special cases with existing literature.

Heat generation effect and failure mechanism of pouch-type lithium-ion battery under over-discharge for electric vehicle

Heat generation is a crucial factor for lithium-ion batteries during the charge and discharge process, which can trigger serious safety issue such as fire hazard and explosion. Over-discharge is a common inducement which can result in not only heat generation effect, but electrode and electrolyte failure. However, it is not definite that the accurate mechanism of heat generation and battery failure triggered by over-discharge. Here, we propose an over-discharge strategy to understand the mechanism of heat generation and battery failure. 36 Ah pouch-type battery is charged at 1C (36 A) current density, and is discharged for 1.5 h at 1C (36 A) with 0.5 h over-discharge degree. The battery was disassembled and analyzed by X-ray diffraction (XRD), Raman test, scanning electron microscopy (SEM) and X-ray photoelectron spectroscopy (XPS). Our results revealed the hidden the heat generation of over-discharge, which is associated with the copper dissolution on anode and deposition on cathode, the degradation of electrolyte under over-discharge process. The proposed method offers a beneficial guidance for researchers to study the over-discharge behaviors of other decomposition reactions.

Numerical analysis of convective transport mechanisms in two-layer ternary (TiO 2 − SiO 2 − Al 2 O 3) Casson hybrid nanofluid flow in a vertical channel with heat generation effects

In this article, we investigate the flow dynamics and convective transport of nanofluid and ternary hybrid nanofluid in a two-layer vertical channel. Employing a Casson model with blood as the base fluid in both layers, the first layer incorporates nanofluid while the second layer comprises ternary hybrid nanofluid Laminar, incompressible flow with extra viscous dissipation effects is included in the formulation of this problem. The velocity and temperature are assumed to be continuous at the interface. The governing equations are converted into non-dimensional equations by using variables in the dimensionless form. The effective method known as homotopy analysis method (HAM) scheme is used to deal with the mathematical formulations. The behavior of velocity and temperature profile is sketched for various physical parameters and Nusselt number variations are tabulated. The results reveal that increasing the value of Eckert number raises the temperature. Temperature rises as and – – nanoparticles volume percentage rises. Nusselt number increases as Eckert number and Prandtl number increases while decreases as Casson parameters increase at the right wall. Rising values of and exhibit dissimilar behavior in the velocity profile. This study could be useful for medical purposes, like making better ways to deliver medicine through our blood vessels to treat cardiovascular diseases.