Analysis Of Heat Transport Research Articles

Numerical analysis of bioconvective heat transport through Casson nanofluid over a thin needle.

Bioconvective flows over a thin needle hold significant importance in various fields, particularly in biomedical engineering, microfluidics, and environmental science. This paper examines the bioconvective flow properties of a copper and blood-based Casson nanofluid over a thin needle, accounting for gyrotactic microorganisms in the presence of a magnetic field. The two-phase nanofluid model is applied to formulate the flow problem. The system of non-dimensional ordinary differential equations is obtained by reducing the governing partial differential equations with the help of similarity variables. Further, the ODEs are numerically solved using the 4th-order Runge-Kutta method based Shooting technique. The similar solutions of the non-dimensional ODEs are represented graphically and the blood-based nanofluid's velocity, temperature, concentration, and presence of microorganisms are examined with reference to the accompanying diagrams. A detailed analysis is provided for skin friction, Nusselt number, and microorganism density number. The primary outcomes reveal that the augmentation of the mixed convection parameter and buoyancy ratio parameter enhance the rate of heat transfer.

Heat transport analysis of three-dimensional magnetohydrodynamics nanofluid flow through an extending sheet with thermal radiation and heat source/sink

Regarding heat transformation efficiency, the hybrid nanofluid performs superior to the nanofluid. The majority of hybrid nanofluid uses are in the industrial sector, producing solar energy, cooling generators, and vehicle heat transformation. Heat transfer and nanofluid velocity are the two most crucial transport properties that must be evaluated before the first and second thermodynamics equations are applied to nanoscale fluids. The objective of this work is to investigate the characteristics of transmission of heat of magnetohydrodynamic (MHD) nanofluid (Ag/H2O)and hybrid nanofluid (Ag+Al2O3/H2O)flow on a linear extensible sheet when magnetic forces are present. Similarity variables are applied to transform a set of nonlinear dimensionless partial-differential equations to collection of ordinary-differential equations. The non-analytical solutions of these transformed equations are found utilizing the MATLAB mathematical program's bvp4c function. The impression of various physical attributes along skin friction coefficients and properties of heat transmission are analyzed. The behavior of key parameters, including surface stretching ratio, rotational and magnetic effects, for temperature and velocity, is shown using graphs and tables. In conclusion, hybrid nanofluids, which comprise silver and aluminum oxide nanoparticles dispersed in water, outperform silver-water nanofluids by around 10–15 % under magnetohydrodynamic (MHD). The higher thermal conductivity of these hybrid nanofluids allows for better heat dissipation, making them an appealing option for applications that need optimal thermal management in the presence of magnetic fields.

Nanoscale heat transport analysis of magnetized trihybrid nanofluid over wedge artery: Keller box and finite element scheme combination

This research represents a crucial step forward in the design and application of magnetized ternary hybrid nanofluids, paving the way for innovations in thermal management and medical treatment technologies. Optimization analysis of nanoscale heat transport for magnetized ternary hybrid bio nanofluid containing SiO2, TiO2, and Al2O3 nanoparticles over a three-dimensional wedge geometry is made in this article. Heat transport analysis is studied through thermal and joule heating effects and the ternary hybrid composition is chosen to leverage the combined thermal properties of the nanoparticles. Furthermore, detail streamlines of flow pattern are investigated for different physical parameters. Physical system is formulated with the system of Partial differential equation (PDEs) and it is processed with similarity transformation to convert it into system of ordinary differential equation (ODEs). Furthermore, Keller box scheme is applied to fetch its numerical solution and compared with finite element technique for validation and found smooth agreement.Temperature is increased with pressure gradient, shear strain and thermal radiation parameter. Magnitude of drag force is increasing with increasing Weissenberg number. For We = 0.2, 0.3, 0.4, 0.5, 0.6, skin friction increases in ternary nanofluid with 13 %,17 %, 21 %, 23 % and 26 % respectively. For β = 0.3, 0.4, 0.5, 0.6, 0.7, skin friction decreases in ternary nanofluid with 30 %,25 %, 20 %, 15 % and 10 % respectively.

Optimization of nanoscale heat transport analysis of ternary hybrid nanofluid over three‐dimensional wedge geometry in magnetized environment

AbstractExponential space‐based heat source with shear‐thinning/thickening behavior offers innovative insights into the optimization of thermal transport process in complex systems, such as in the cooling of microelectronics, energy storage technologies, and biomedical devices, where accurate thermal control is critical. This study explores the investigation of an exponential space‐based heat source with effects of shear thinning/thickening behavior of a ternary infinite shear rate viscosity‐dependent Carreau water‐based nanofluid [Cu, Fe3O4, SiO2] over a three‐dimensional wedge in a magnetized environment. The interaction between heat transport and magnetic fields is explored through the behavior of the ternary nanofluid by classifying the both shear‐thinning and shear‐thickening effects. The incorporation of physical assumptions in the model gives the set of partial differential equations (PDEs) and similarity transformations are launched to convert them into ordinary differential equations (ODEs). Furthermore, bvp4c scheme is used to fetch the numerical solution. Temperature profile is increasing with exponential‐based source heat parameter due to a reduction in the rate of heat absorption by the fluid. Ternary nanofluids exhibit the highest rate of temperature increment due to the effects of multiple nanoparticles as compared to hybrid or single‐nanoparticle nanofluids. Rate of velocity decrement in ternary nanofluids compared to bi‐hybrid nanofluids and single‐particle nanofluids.

Brownian motion in a magneto Thermo-diffusion fluid flow over a semi-circular stretching surface

The current study explores the mass and heat transport analysis of a Casson liquid stream past a curved surface. The current model considers the effect of magnetic strength brought on by the strength of the applied uniform magnetic field. The significance of thermophoresis and Brownian motion are also taken into account using the Buongiorno nano-liquid model. The study of liquid flow over stretching sheets frequently addresses practical issues that have garnered significant attention from researchers due to their importance in various domains, including microfluidics, fibreglass production, manufacturing, transportation, metal extrusion, thermal insulation, glass production, paper manufacturing, and acoustic blasting. The governing partial differential equations (PDEs) are converted into ordinary differential equations (ODEs) using the similarity variables. These equations are numerically solved using the finite difference method (FDM). The concentration, temperature, and velocity graphs were produced by varying the different physical parameters. The upsurge in the magnetic parameter reduces the velocity profile. As the magnetic parameter increases, thermal and concentration profiles upsurge. The decrease in velocity profile can be seen as the Casson parameter rises. The intensification in values of thermophoretic parameter enhances the thermal and concentration profiles. The concentration and thermal profiles reduce as the curvature parameter upsurges.

On the thermal performance of a three-dimensional cross-ternary hybrid nanofluid over a wedge using a Bayesian regularization neural network approach

Abstract Significance Studying the flow of ternary nanofluids [Ag, Cu, MoS2] holds significant importance in both science and engineering. Ternary nanofluids are vital in advancing thermal management systems, heat exchangers, aerospace, and materials processing applications. Purpose This study investigates the ternary hybrid Carreau nanofluid numerically for thermal proficiency in the inclined magnetized environment. In this study, three distinct nanoparticles of [Ag, Cu, MoS2] and base fluid water over the wedge are used. The velocity of nanofluids is judged under the influence of an inclined magnetic field, and the thermal performance is scrutinized by incorporating the thermal radiation effect. Methodology The physical problem generates partial differential equations, which are transformed into ordinary differential equations (ODEs) through similarity variables. These ODEs are linearized into a system of ODEs and then passed under the bvp4c Matlab program to get the solution. This solution is again trained by an artificial neural network, and further results are obtained with both schemes and compared. Findings The most rapid heat transport analysis is found for ternary hybrid nanofluids compared to bi-hybrid nanofluids. The thermal radiation parameters and the magnetic environment augment the rate of heat transport.

Quadratic regression model for response surface methodology based on sensitivity analysis of heat transport in mono nanofluids with suction and dual stretching in a rectangular frame

Quadratic regression model for response surface methodology based on sensitivity analysis of heat transport in mono nanofluids with suction and dual stretching in a rectangular frame

Streamlines and neural intelligent scheme for thermal transport to infinite shear rate for ternary hybrid nanofluid subject to homogeneous-heterogeneous reactions

SignificanceThe CuO, Al2O3, and TiO2 nanoparticles find extensive applications in advanced chemical reaction-based thermal transport and quadratic convective nanofluids due to their exceptional thermal properties and chemical stability. Increased thermal conductivity of these nanoparticles used to enhance heat transfer in various chemical reactors, resistance to chemical degradation and photocatalytic reactors and solar energy applications. MotiveThis study brings the investigation about quadratic convection-based thermal transport to infinite shear rate for magnetized ternary radiative cross nanofluid with homogeneous-heterogeneous chemical reactions. Water is taken as base fluid and three nanoparticles are Copper oxide (CuO), aluminium oxide (Al2O3), and titanium dioxide (TiO2). Heat transport analysis is made through quadratic convection, magnetic field and thermal radiation. Concentration of nanofluid is scrutinized though homogeneous-heterogeneous chemical reactions. Methodology: Physical problem with assumptions generates the system of partial differential equations (PDEs) and these PDEs are transformed into ordinary differential equations (ODEs) through similarity variables. Furthermore, a unique combination of Bvp4c and Levenberg Marquardt neural network (LM-NN) schemes is utilized to fetch the numerical solutions. Bvp4c is utilized to solve the governing equations, while LM-NN serves to enhance predictive capabilities and capture intricate nonlinear relationships. FindingsMagnetic environment, chemical process, radiations effects and volumetric fraction of nanoparticles make better heat transfer efficiency and control.

Quantitative analysis of interface heat transport at the Si3N4/SiO2 van-der Waals point contact

Si3N4 and SiO2 have been widely used in lithium batteries and optical devices. The high energy density brought by device integration makes the interfacial heat transport at the nano scale a hot spot. To optimize interfacial heat transfer, the roughness of the device surface is continuously reduced down to the nanometer. However, due to the limitation of spatial resolution, it is difficult to realize the measurement of thermal boundary resistance in the case of nanoscale contact by the existing measurement means. There is a great discrepancy between the measurement and simulation results, making the optimization of interfacial heat transfer lack of experimental verification. In this paper, the measurement of thermal boundary resistance of Si3N4/SiO2 interface at the nano-scale, was firstly realized by the optimized 3ω-SThM system. The effect of air tunnel on the heat transfer between real surfaces was also analyzed. The progress made so far provides an effective experimental tool to measure interfacial heat transport at nanoscale point contact.

Neural intelligent approach for heat transfer applications of trihybrid cross bio-nanofluid over wedge geometry

Significance: Heat transport in the blood within a wedge-shaped artery is significant in biomedical engineering field like develop therapeutic strategies, drug delivery to specific regions of the artery, vicinity of narrowed or blocked arteries and catheter-based treatments such as angioplasty or thermal ablation. Motive: This study investigates the heat transport analysis of trihybrid nanofluid (blood) over wedge-shaped artery with mathematical model of Cross fluid. This study incorporates three nanoparticles, graphene oxide (GO), titanium dioxide (TiO2), and aluminum oxide (Al2O3) in base fluid blood. The wedge-shaped artery is chosen due to its relevance to biomedical applications and it reflects the nature of blood flow in real vascular structures. Heat transport is scrutinized through thermal radiations and flow rate is inspected through inclined magnetic field. Methodology: The bvp4c and Levenberg–Marquardt Neural Network (LM-NN) supervised neural scheme is used to predict the numerical outcome of this study. Findings: Incorporation of nanoparticles made rapid heat transport of blood in wedge-shaped artery. Velocity of blood is decreased with high Weissenberg number and magnetic force. The temperature of a blood in a wedge-shaped artery increases with positive non-uniform heat source/sink parameters and decreases with negative non-uniform heat source/sink parameters.

Computational assessment of flow and heat transfer characteristics through Cu + Al2O3 + TiO2 ternary hybrid nanomaterial host-water with shape effect

ABSTRACT Solar energy stands out as a vital source of thermal power derived from the sun. Its capacity finds applications across various technological domains, including photovoltaic panels, solar vehicles, solar lighting infrastructure, and solar water pumps. The contemporary landscape emphasizes the integration of solar energy in industries, notably exemplified by the prevalence of solar-powered charging stations. This article proposes a new perspective on heat transport analysis, incorporating the shape effect on the ternary hybrid nanofluid model along with considerations of thermal radiation, Cattaneo–Christov heat flux factor, heat source, and sink. For the evaluation, three differently shaped ternary hybrid nanoparticles are taken into account including platelet-shaped Cu , cylindrical-shaped A l 2 O 3 , and disc-shaped Ti O 2 . Through boundary layer approximations, the contributions of radiation, heat source, and sink variables are implemented into the regulating equations. The redesigned ordinary differential equations are numerically solved employing the NDSolve method after treating similarity variables. In the case of physical quantities, multiple linear regression is introduced to discover solutions for the flow elements. Augmentation in the momentum of dissimilarly shaped Cu , A l 2 O 3 and Ti O 2 nanoparticles enhance the velocity of ternary hybrid nanofluid flow more than that of spherical-shaped nanoparticles. The significant heat transfer is observed in mono, hybrid and ternary nanofluids with the existence of radiation and heat source phenomena. The multiple linear regression precisely forecasted the physical quantities with the error 10 − 3 . An application of a ternary hybrid nanofluid in a solar powered charging station can efficiently perform and successfully address an energy crisis by exhibiting an acceptable amount of power. This capability contributes to the reliable charging of electronic devices. Also, the machine learning technique can reliably and accurately perform the heat transfer analysis.

Artificial neural computing and statistical analysis of heat and mass transport of nanofluid flow with melting heat and thermal stratification

The melting heat phenomenon in viscous nanofluid MHD flow over a stretching sheet with variable porosity and permeability was utilized. The behavior of magneto-viscous nanofluid flow was scrutinized using the concepts of machine learning and statistics. Thermal stratification, heat source, and activation energy in the solution of tween-20 nanoparticles and an ethyl-acetate base-type fluid are examined. Brownian and thermophoretic phenomena are included. Non-linear partial differential equations (PDEs) are converted into non-linear ordinary differential equations (ODEs) via von Karman similarity variables. Dataset is generated by the 4th-order Runge-Kutta numerical method for the artificial neural network. The ratio parameter and melting parameter enhance the velocity outline, while the melting parameter and thermal stratification parameter reduce the temperature outline. An increase in the concentration outline is seen with the activation energy parameter and Brownian motion parameter both increase the concentration outline. The system's performance using metrics like regression analysis, mean squared error, and error histograms is evaluated. The impact of these factors on significant results, such as the drag coefficient and heat transfer rate, is statistically investigated using multiple linear regressions. The integration of statistical and machine learning methods is deemed crucial for enhancing understanding of complex fluid dynamics in magnetic nanofluid flows.

Magnetohydrodynamic Marangoni fluid flow, heat, and mass transfer over a radially stretching disk in the presence of heat generation and chemical reaction

The analysis of magnetohydrodynamic (MHD) Marangoni fluid flow, heat, and mass transport over a disk is considered in this article. The fluid is assumed to pass radially over a stretching disk. Suction/blowing at the boundary, internal heat generation/absorption, and a first-order chemical reaction are also considered. By using appropriate similarity transformations, the governing nonlinear partial differential equations (PDEs) are transformed into ordinary differential equations (ODEs). These ODEs along with the appropriate boundary conditions for the model are solved numerically by a shooting technique using MATHEMATICA software. The obtained results are compared with the available results in the literature for some special cases. The effects of the magnetic parameter, the Marangoni number, Marangoni ratio parameter along with the other pertinent parameters on fluid flow, heat and mass transport are analyzed and discussed in detail. It is noted that higher magnetic field depresses the fluid velocity whereas the fluid temperature and fluid concentration are uplifted with an increase in the magnetic field parameter. A quite opposite behavior is observed for Marangoni number. Marangoni ratio parameter boosted the fluid velocity as well as the fluid concentration and the temperature. Also externally applied suction significantly affects the fluid behavior. Increasing chemical reaction parameter reduces the fluid concentration. It is observed that a maximum increase in the Nusselt number occurs for Marangoni parameter Ma, which is 34.75595% when the suction/injection parameter s = 0.5. Also, for Marangoni ratio parameter Ra, a maximum increase in Nusselt number occurs, which is 6.7884% when suction/injection parameter s = 0.5.

Heat transport analysis of nanoliquid in a microchannel with aggregation kinematics: a modified Buongiorno model approach

ABSTRACT Convective heat transmission of Ti O 2 − EG nanoliquid under slip and convective regime in a microchannel is examined using a modified Buongiorno model. The fractal-based approach is employed to describe the aggregation of nanoparticles. The impact of molecular dynamics, particularly on dynamic viscosity and thermal conductivity due to the aggregation of nano-sized particles, is simulated with the help of two significant models: namely, the Krieger-Dougherty model and the Maxwell-Bruggeman model, respectively. The aspect of the interfacial layer enables us to get a realistic nanoliquid model. The solutions for the designed nondimensional mathematical model are obtained numerically. The variation in flow and thermal distribution for pertinent parameters are visualized graphically. The study reveals that the thermophysical characteristics sturdily depend on nanoparticle concentration and cluster formation. It is emphasized that the viscous dissipation and radiative heat transfer contribute towards magnifying the irreversibilities in a microchannel. The findings are useful in bioconvection and various heat transfer applications.

Numerical analysis of inclined magnetic force impact on cross liquid flowing with widening shallow and heat generating

ABSTRACT The creation, utilisation, conversion, and exchange of thermal energy are all covered under the thermal engineering subject of heat transfer. Heat transfer plays a major role in engineering and industrial sectors like food packaging, food additive manufacturing, electronic cooling, microturbine, etc. Scientists across the world have tried to explore the impact of heat transfer on fluid past an expandable surface due to its exciting applications in industries like polymer production, paper production, crystal glass manufacturing, etc. This article has unique exploration, and it emphasises interpreting the Cross fluid flow along stretching surface with convective heat transport analysis by using the Lie group methodology. We investigated the implication of inclined upper-convected Maxwell fluid magnetohydrodynamic (MHD) movement through a penetrable strained plate. To solve nonlinear differential equations and clearly determine their absolute invariants, the Lie group approach is introduced. For the numerical solution of non-linear ordinary differential equations with boundary conditions, the fourth-order Runge–Kutta procedure with shelling performance is utilised. Plots showing the impacts of motivated and non-motivated MHD are researched and examined for the alterations of many parameters, and statistical graphs are given to explain the physical values. It is evident that opposing behaviour occurs in connection to temperature captivation and generation parameters together with motivated and non-motivated MHD. Under an amplified, heat-generating parameter and Deborah number, the rate of heat transmission increases. The Lie group investigation of Cross liquid in the presence/absence of inclined and non-inclined has not been investigated yet in the available literature.

Study on heat transport analysis and improvement method in a single CaCO3 pellet for thermochemical energy storage

CaCO3/CaO thermochemical energy storage (TCES) pellets have significant advantages in bulk energy storage density, transport, and utilization. However, severe heat transport limitations within the milli-sized CaCO3 significantly affect the TCES efficiency and economy. Currently, investigations on the effect of initial porosity, bulk gas flow velocity, and reaction rate on heat transport and methods of enhancing the heat transport inside the pellet are lacking. In this paper, we developed a mathematical model coupling calcination reaction, mass transfer, and heat transfer to reveal the effects of pellet parameters and operating conditions on heat transport and reaction conversion rate within a CaCO3 pellet. The results show that the size of the CaCO3 pellet, bulk gas temperature, and reaction rate generate the most pronounced impacts on heat transport in a single CaCO3 particle during the TCES process. Furthermore, the heat transport inside the CaCO3 pellet can be improved by appropriately increasing the bulk gas flow velocity. Finally, this paper first numerically investigates the addition of SiC as a thermal conductivity enhancer to improve the heat transport performance inside a CaCO3 pellet. This study can guide the design of high-performance CaCO3 composite pellets and inform the selection of operating conditions for subsequent reactor applications.

Constraint-based analysis of heat transport and irreversibility in magnetic nanofluidic thermal systems

Purpose This paper aims to investigate the thermal performance of equivalent square and circular thermal systems and compare the heat transport and irreversibility of magnetohydrodynamic (MHD) nanofluid flow within these systems. Design/methodology/approach The research uses a constraint-based approach to analyze the impact of geometric shapes on heat transfer and irreversibility. Two equivalent systems, a square cavity and a circular cavity, are examined, considering identical heating/cooling lengths and fluid flow volume. The analysis includes parameters such as magnetic field strength, nanoparticle concentration and accompanying irreversibility. Findings This study reveals that circular geometry outperforms square geometry in terms of heat flow, fluid flow and heat transfer. The equivalent circular thermal system is more efficient, with heat transfer enhancements of approximately 17.7%. The corresponding irreversibility production rate is also higher, which is up to 17.6%. The total irreversibility production increases with Ra and decreases with a rise in Ha. However, the effect of magnetic field orientation (γ) on total EG is minor. Research limitations/implications Further research can explore additional geometric shapes, orientations and boundary conditions to expand the understanding of thermal performance in different configurations. Experimental validation can also complement the numerical analysis presented in this study. Originality/value This research introduces a constraint-based approach for evaluating heat transport and irreversibility in MHD nanofluid flow within square and circular thermal systems. The comparison of equivalent geometries and the consideration of constraint-based analysis contribute to the originality and value of this work. The findings provide insights for designing optimal thermal systems and advancing MHD nanofluid flow control mechanisms, offering potential for improved efficiency in various applications. Graphical Abstract

Thermal analysis of heat transport in a slip flow of ternary hybrid nanofluid with suction upon a stretching/shrinking sheet

Understanding heat transfer in slip flow scenarios involving a stretching or shrinking sheet has immediate applications in numerous fields, including materials processing, production, and temperature management systems. This information supports the development of novel heat transfer methods and systems. Therefore the present study focuses on stagnant point flow and discusses the dynamics and thermal characteristics of ternary hybrid nanofluids with the application of Tiwari and Das nanofluids. It is assumed that the ternary hybrid nanofluids are present on a stretching/shrinking sheet. The slipping effects and suction boundary conditions are implemented. The simulation will be performed using the finite element method with the software package COMSOL Multiphysics 6.0. The system of ordinary differential equations (ODEs) obtained through similarity transformation will be solved numerically to obtain simulation results. The average velocity, temperature profiles, and Nusselt number patterns using non-dimensional parameters are also analyzed. These non-dimensional parameters include the stretching/shrinking parameter, ranging from −1 to 0.5, and the suction parameter and slip flow parameter, both ranging from 0 to 2. The ternary hybrid nanofluids under investigation consist of a combination of TiO2, Silver-Ag, and ZnO particles in a base fluid (water). The volume fraction of these particles in the base fluid will be tested from 0.03 to 0.3. It was found that when there are no suction and no slipping effects, the Nusselt number decreases for the shrinking case and increases for the stretching case. It is also concluded that when there is no suction or slipping effect, the average temperature profile increases in the shrinking case and decreases in the stretching case.

Non-local modelling of freezing and thawing of unsaturated soils

A large part of the earth’s surface is covered by seasonally or permanently frozen soils. Considering the negative impact of climate change, future development of such regions can be underpinned by mathematical methods for accurate analysis of heat and moisture transport in freezing and thawing soils. Reported in this paper is a novel non-local formulation of water and heat transport in unsaturated soils. The formulation uses bond-based peridynamics (PD) and consists of a set of integral–difference formulations of energy and mass conservation. Specific features of freezing/thawing soils are incorporated by a combination of van Genuthcen and Clausius–Clapeyron relations. Computational results are compared with four sets of laboratory experiments to demonstrate the efficiency of the developed approach. The model can be used to analyse the effect of water flow on heat transfer in soils during thawing of permafrost soils. Further, it can be applied in modelling climate change effects, and can be used for construction of coupled physically justified models of frost heave.

Numerical Investigation of Ternary Hybrid Non‐Newtonian Nanofluids and Heat Transport Over an Inclined Shrinking Sheet Utilizing Artificial Neural Network

The purpose of the study is to investigate the thermal proficiency of a trihybrid magnetized water‐based cross nanofluid over an inclined shrinking sheet. Cross‐fluid is the best model to investigate the fluid flow at a very high and very low share rate. There are three nanoparticles that are added in based fluid (water) to form the requisite posited ternary hybrid nanofluid. Moreover, heat transport analysis is scrutinized by incorporating the melting conditions. The obtained nonlinear system of partial differential equations (PDEs) from assumed physical assumption is converted into the nonlinear setup of ordinary differential equations (ODEs). These ODEs are passed under the boundary value problem of a fourth‐order (bvp4c) MATLAB program for numerical results. With the help of bvp4c, data are further trained through an artificial neural network and results are predicted. Results are compared with both techniques and found smooth agreement. The obtained numerical results provide valuable insight for optimizing heat transfer processes involving nanoparticle‐enhanced fluid on inclined shrinking sheets. From the results, it is concluded that the inclusion of nanoparticles enhances the viscosity and thermal conductivity of the fluid. High temperatures make rapid heat transfer scenarios.