Entropy Generation Optimization Research Articles

Local entropy generation optimization and thermodynamic irreversibility analysis of oval-shaped coaxial ground heat exchangers: A detailed numerical investigation

Optimizing the heat transfer and thermodynamic efficiency of Ground Heat Exchangers (GHE) is crucial for maximizing the energy efficiency of Ground-coupled Heat Pump (GCHP) systems utilized in building heating and cooling applications. This study pioneers an effective approach of both the first and second laws of thermodynamics of the newly oval-shaped coaxial GHEs (oval-CGHEs), assessing heat transfer, thermohydraulic performance, and local entropy generation rate to explore the optimum design and operational conditions for heat exchange maximization and entropy generation minimization. Utilizing a three-dimensional numerical model validated by experimental results, this study examines the trade-offs between heat transfer improvements and entropy generation rate intensification of the oval-CGHEs in comparison to the typical circular-shaped CGHE (circle-CGHE) further than exploring the effect of key operational and design parameters and performing sensitivity analysis. The results reveal that oval-CGHEs exhibit higher irreversibility as a penalty for their superior heat transfer capabilities compared to traditional circular-shaped CGHEs (circle-CGHE), which can be mitigated by optimizing the position of the inner tube. Moreover, the study underscores the criticality of maintaining a balance between enhanced heat transfer and the associated rise in irreversibility, particularly concerning the factors of mass flow rates and installation depths.

Electroosmotic MHD ternary hybrid Jeffery nanofluid flow through a ciliated vertical channel with gyrotactic microorganisms: Entropy generation optimization

In this study, the computational analysis of entropy generation optimization for synthetic cilia regulated ternary hybrid Jeffery nanofluid (Ag–Au–TiO2/PVA) flow through a peristaltic vertical channel with swimming motile Gyrotactic microorganisms is investigated. Understanding the intricate interaction of multiple physical phenomena in biomedical applications is essential for optimizing entropy generation and advancing microfluidic systems. The characteristics of nanofluid are explored for the electroosmotic MHD fluid flow in the presence of thermophoresis and Brownian motion, viscous dissipation, Ohmic heating and chemical reaction. Using the appropriate transformations, a set of ordinary differential equations are created from the governing partial differential equations. The resulting ODEs are numerically solved using the shooting technique using BVP5C in MATLAB after applying the long-wavelength and low Reynolds number approximation. The velocity, temperature, concentration, electroosmosis, and microorganism density profiles are analyzed graphically for different emerging parameters. Graphical investigation of engineering interest quantities like heat transfer rate, mass transfer rate, skin friction coefficient, and entropy generation optimization are also presented. It is observed that the rate of mass transfer increases for increasing thermophoretic parameter, while reverse effect is noted for Brownian motion parameter, Schmidt number, and chemical reaction number. The outcomes of present study can be pertinent in studying Cilia properties of respiratory tract, reproductive system, and brain ventricles.

Statistical analysis of radiative solar trough collectors for MHD Jeffrey hybrid nanofluid flow with gyrotactic microorganism: entropy generation optimization

PurposeA parabolic trough solar collector is an advanced concentrated solar power technology that significantly captures radiant energy. Solar power will help different sectors reach their energy needs in areas where traditional fuels are in use. This study aims to examine the sensitivity analysis for optimizing the heat transfer and entropy generation in the Jeffrey magnetohydrodynamic hybrid nanofluid flow under the influence of motile gyrotactic microorganisms with solar radiation in the parabolic trough solar collectors. The influences of viscous dissipation and Ohmic heating are also considered in this investigation.Design/methodology/approachGoverning partial differential equations are derived via boundary layer assumptions and nondimensionalized with the help of suitable similarity transformations. The resulting higher-order coupled ordinary differential equations are numerically investigated using the Runga-Kutta fourth-order numerical approach with the shooting technique in the computational MATLAB tool.FindingsThe numerical outcomes of influential parameters are presented graphically for velocity, temperature, entropy generation, Bejan number, drag coefficient and Nusselt number. It is observed that escalating the values of melting heat parameter and the Prandl number enhances the Nusselt number, while reverse effect is observed with an enhancement in the magnetic field parameter and bioconvection Lewis number. Increasing the magnetic field and bioconvection diffusion parameter improves the entropy and Bejan number.Originality/valueNanotechnology has captured the interest of researchers due to its engrossing performance and wide range of applications in heat transfer and solar energy storage. There are numerous advantages of hybrid nanofluids over traditional heat transfer fluids. In addition, the upswing suspension of the motile gyrotactic microorganisms improves the hybrid nanofluid stability, enhancing the performance of the solar collector. The use of solar energy reduces the industry’s dependency on fossil fuels.

ENERGY EFFICIENCY IMPROVEMENT AND ENTROPY GENERATION MINIMIZATION THROUGH STRUCTURAL OPTIMIZATION OF A DOUBLE-LAYER LIQUID-COOLED PLATE WITH CIRCULAR ARC-SHAPED FLOW CHANNELS

Power batteries for new energy vehicles and other high-power electrical devices benefit greatly from liquid-cooled plates for thermal control. In the present work, a liquid-cooled plate with a double-layer arc-channel structure is developed to achieve a uniform temperature distribution on the surface of lithium-ion powered batteries and to reduce operating temperatures. Numerical simulations are employed to examine the flow properties and heat transfer capabilities of the plate. Subsequently, the model is validated experimentally. The structure of the liquid-cooled plate is optimized using a genetic algorithm. In the research, two methods for optimizing the structure of liquid-cooled plates have been proposed based on defining the fitness function of genetic algorithms. The first method uses a dimensionless number to represent the amount of pump power needed to allow the working fluid to absorb one joule of heat energy. The other method uses the entropy generation of the liquid-cooled plate as the fitness function of genetic algorithms. Genetic algorithms may be used to find the minimum dimensionless number and the minimal amount of entropy. The structural characteristics of the liquid-cooled plate may be obtained with the best energy efficiency and the least amount of entropy production using the dimensionless number minimization (DNM) and entropy generation (EGM) optimization techniques, respectively. The performance of the two optimization techniques is contrasted. The maximum temperature of the plate is reduced by 2.58 K and 0.14 K, and the standard deviation of the temperature is reduced by 0.685 K and 0.408 K after the optimization using the creatively established dimensionless number and the entropy generation minimization methods, respectively. The pump work required by the working fluid to absorb one joule of heat energy from the plate is reduced by 70.5% and 12.1%. At two distinct boundary conditions, the proposed liquid-cooled plate outperforms the plates with serpentine and parallel channels in terms of cooling performance or energy efficiency.

Computer simulation of two phase power-law nanofluid of blood flow through a curved overlapping stenosed artery with induced magnetic field: entropy generation optimization

PurposeThe purpose of this study is to determine the impact of two-phase power law nanofluid on a curved arterial blood flow under the presence of ovelapped stenosis. Over the past couple of decades, the percentage of deaths associated with blood vessel diseases has risen sharply to nearly one third of all fatalities. For vascular disease to be stopped in its tracks, it is essential to understand the vascular geometry and blood flow within the artery. In recent scenarios, because of higher thermal properties and the ability to move across stenosis and tumor cells, nanoparticles are becoming a more common and effective approach in treating cardiovascular diseases and cancer cells.Design/methodology/approachThe present mathematical study investigates the blood flow behavior in the overlapped stenosed curved artery with cylinder shape catheter. The induced magnetic field and entropy generation for blood flow in the presence of a heat source, magnetic field and nanoparticle (Fe3O4) have been analyzed numerically. Blood is considered in artery as two-phases: core and plasma region. Power-law fluid has been considered for core region fluid, whereas Newtonian fluid is considered in the plasma region. Strongly implicit Stone’s method has been considered to solve the system of nonlinear partial differential equations (PDE’s) with 10–6 tolerance error.FindingsThe influence of various parameters has been discussed graphically. This study concludes that arterial curvature increases the probability of atherosclerosis deposition, while using an external heating source flow temperature and entropy production. In addition, if the thermal treatment procedure is carried out inside a magnetic field, it will aid in controlling blood flow velocity.Originality/valueThe findings of this computational analysis hold great significance for clinical researchers and biologists, as they offer the ability to anticipate the occurrence of endothelial cell injury and plaque accumulation in curved arteries with specific wall shear stress patterns. Consequently, these insights may contribute to the potential alleviation of the severity of these illnesses. Furthermore, the application of nanoparticles and external heat sources in the discipline of blood circulation has potential in the medically healing of illness conditions such as stenosis, cancer cells and muscular discomfort through the usage of beneficial effects.

Entropy Generation Optimization in an Unsteady Hybrid Nanofluid Flow Over a Flat Plate with Variable Viscosity: A Cattaneo-Christov Heat Flux Model

Nanofluids are a novel and intriguing class of heat transmission fluids that can be used in place of more conventional options. They have several applications, including fuel cells, heat exchangers, and the pharmaceutical industry. When it comes to heat transport, hybrid nanofluids much outperform their mono-fluid counterparts. These are being put to use in a wide variety of areas, from solar power to air conditioning. Unsteady flow characteristics of a hybrid nanofluid (Ethylene Glycol + ZnO + TiO2) over a flat plate at varied Lorentz forces, volume fraction of nanoparticles, and thermal radiation are unknown when variable viscosity is taken into account. Paper’s novelty is addressing this gap, which is to examine the impact of variable viscosity on the hybrid nanofluid flow by a flat plate under convective boundary condition when thermal radiation and magnetic field are significant. Cattaneo and Christov’s heat flux model is used to analyse the phenomenon of heat transfer. This paper also includes an analysis of irreversibility. The equations required to represent the problem have been turned into a system, and this system has been solved using the bvp4c solver. Validated the results (of engineering parameters including friction coefficient) obtained using the bar graphs by using Multiple linear regression. It has been observed that the thermal relaxation parameter (Γ) and the unsteady parameters (S) both have similar effects on the heat transmission rate. It is found that there is an increment of 0.001278 (when 0 ≤ Γ ≤ 0.6) and 0.103865 (when 0.4 ≤ S ≤ 1) in the Nusselt number. It is clear from a closer inspection that as magnetic field parameter (Mg) and viscosity parameters (δ) are raised, the friction factor declines. It is observed that, at 0 ≤ Mg ≤ 1.8, friction factor declines at a proportion of 0.08974. It is detected that higher Brinkman number values lead to a greater rate of entropy generation and an upsurge in the (temperature-dependent) viscosity parameter contributes to a decline in the same. As the viscosity parameter is amplified, it is also seen that the fluid’s velocity declines.

Entropy generation analysis and optimization of cooling systems in industrial and engineering operations

AbstractEfficient cooling is crucial for maintaining the reliability and performance of industrial and engineering systems that generate excess heat. Entropy generation analysis, established on the second law of thermodynamics, plays a vital role in identifying inefficiencies within these systems and improving their overall efficiency. This study focuses on a theoretical investigation of the entropy generation, considering the cumulative impact of surface slipperiness, Brownian motion, applied magnetic field, thermophoresis on the nanofluid flow toward a convective heated stretching surface. The governing model partial differential equations undergo a transformation through similarity transformation, resulting in a nonlinear ordinary differential equation. This equation is subsequently solved numerically by employing the Runge–Kutta–Fehlberg integration scheme in conjunction with the shooting method. The obtained results reveal the influence of various parameters on the temperature, velocity, Nusselt number, skin friction, Sherwood number, Bejan number, nanoparticle concentration, and entropy generation. Upon analysis, it was notable that the introduction of a magnetic field, higher Biot numbers, Eckert numbers, and elevated Brownian motion led to an increase in the entropy generation within the system. Conversely, the presence of thermophoresis and reduced surface slipperiness resulted in a decrease in entropy. These results are presented through graphical representations, tables, and quantitative discussions, providing valuable insights for optimizing the cooling and performance of industrial and engineering systems.

Optimization of entropy generation and thermal mechanism of MHD hybrid nanoliquid flow in a sinusoidally heated porous cylindrical chamber

The present computational investigation explores the fluid and thermal characteristics along with entropy generation due to buoyancy-driven magnetohydrodynamic (MHD) convective flow of aqueous hybrid nanoliquid filled in a nonuniformly heated porous cylindrical chamber. The fluid motion in the enclosure is modeled by Brinkman — extended Darcy model. The modeled equations are resolved by finite difference approach. The computations are conducted for Rayleigh number (103–105), Hartmann number (0–50), Darcy number (10−5–10−1), different nanoparticle shapes and nanoparticle volume fraction (Ag/MgO: 0–0.05) to understand the characteristic of flow, thermal and irreversibility distribution. With vast numerical simulations, the outcomes reveal that though the buoyancy force is greater, the fluidity cannot be enhanced unless the permeability and magnetic field strength are optimally maintained. As Ra,Ha and Da is varied respectively from 103 to 105, 50 to 0 and 10−5 to 10−1, the fluidity has been enhanced by 99.39%,83.26% and 99.79%. Among all considered parametric combinations, it has been noticed that the choice of Ha=0,Ra=105,Da=10−1 with proper ratio of nanoparticles enhance the system efficiency. However, minimal entropy generation can be achieved with greater Hartmann and lower Darcy numbers. Furthermore, it has been found that blade shaped nanoparticles lead to increase the performance of thermal system.

Multi-objective optimization of electrokinetic energy conversion efficiency and entropy generation for streaming potential driven electromagnetohydrodynamic flow of couple stress Casson fluid in microchannels with slip-dependent zeta potentials

The present study develops a new mathematical approach to the pressure-mediated streaming potential flow of couple-stress Casson fluids with the influence of slip-dependent zeta potential between two parallel plates in a microchannel. The lateral electric and transverse magnetic fields are externally applied to control the fluid flow. A multi-objective optimization technique was implemented by utilizing the non-dominated sorting genetic algorithm (NSGA-II) by varying different constraints to maximize the electrokinetic energy conversion efficiency and minimize the irreversibility of the system. The present results show that the couple stress and Casson parameters influence the development of streaming potential, electrokinetic energy conversion (EKEC) efficiency, temperature, Nusselt number, and Bejan number for asymmetric velocity slip and temperature jump circumstances. The viscous dissipation, Joule heating, and thermal radiation parameters significantly affect the heat transfer. According to the present results, the EKEC efficiency increases with a slip-dependent zeta potential of couple stress Casson fluid, couple stress fluid, Casson fluid, and Newtonian fluid by 45.92 %, 47.10 %, 42.81 %, and 37.68 %, respectively, compared to that for the slip-independent zeta potential. At the centre of the microchannel for the jump boundary conditions, temperature increases by 2.95 % compared to no jump boundary conditions.

Entropy generation optimization for the electroosmotic MHD fluid flow over the curved stenosis artery in the presence of thrombosis

The present study deals with the entropy generation analysis on the flow of an electrically conductive fluid (Blood) with hbox {Al}_2hbox {O}_3-suspended nanoparticles through the irregular stenosed artery with thrombosis on the catheter. The fluid flow can be actuated by the interactions of different physical phenomena like electroosmosis, radiation, Joule heating and a uniform radial magnetic field. The analysis of different shapes and sizes of the nanoparticle is considered by taking the Crocine model. The velocity, temperature, and concentration distributions are computed using the Crank–Nicholson method within the framework of the Debye–Huckel linearization approximation. In order to see how blood flow changes in response to different parameters, the velocity contour is calculated. The aluminium oxide nanoparticles employed in this research have several potential uses in biomedicine and biosensing. The surface’s stability, biocompatibility, and reactivity may be enhanced by surface engineering, making the material effective for deoxyribonucleic acid sensing. It may be deduced that the velocity profile reduces as the nanoparticle’s size grows while depicts the reverse trend for the shape size. In a region close to the walls, the entropy profile decreases, while in the region in the middle, it rises as the magnetic field parameter rises. The present endeavour can be beneficial in biomedical sciences in designing better biomedical devices and gaining insight into the hemodynamic flow for treatment modalities.

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

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

Entropy generation optimization in a radiative hybrid nanofluid (engine oil + NiZnFe2O4 + MnZnFe2O4) flow through a convectively heated microchannel with cross-diffusion effects

Entropy generation optimization in a radiative hybrid nanofluid (engine oil + NiZnFe2O4 + MnZnFe2O4) flow through a convectively heated microchannel with cross-diffusion effects

Bayesian regularization networks for micropolar ternary hybrid nanofluid flow of blood with homogeneous and heterogeneous reactions: Entropy generation optimization

This study aims to analyze a Bayesian regularization backpropagation algorithm for micropolar ternary hybrid nanofluid flow over curved surfaces with homogeneous and heterogeneous reactions, Joule heating and viscous dissipation. The ternary hybrid nanofluid consists of nanoparticles of titanium oxide (TiO2), copper oxide (CuO), and silicon oxide (SiO2), with blood as the base fluid. The governing partial differential equations for the fluid flow are converted into ordinary differential equations using a group of self-similar transformations. The ordinary differential equations are solved using an appropriate shooting algorithm in MATLAB. The effects of physical parameters including curvature, micro-polar, radiation, magnetic, Prandtl, Eckert, Schmidt, and homogeneous and heterogeneous chemical reaction parameters are analyzed for velocity, micro rotational, temperature, and concentration profile. Physical quantities of engineering interest like heat transfer rate, mass transfer rate, skin friction coefficient, couple stress coefficient, and entropy generation are also discussed in this study. A Bayesian regularization backpropagation algorithm is also designed for the solution of the ordinary differential equations. The obtained network is analyzed using training state, performance, error histograms, model response, Error autocorrelation, and input-error correlation plots. It is observed that the entropy generation and the Bejan number increase for enhancing Brinkman and radiation parameter. Clinical researchers and biologists may use the results of this computational study to forecast endothelial cell damage and plaque deposition in curved arteries, by which the severity of these conditions can be reduced.

Thermal-Hydraulic and Entropy Generation Optimization of Capsule-Type Plate Heat Exchangers With Spherical Dimples

The capsule-type plate heat exchanger (PHE) is a new type of equipment with great potential, which is characterized by the concave and convex capsule-like surface. In this article, new structures consisting of capsules and spherical dimples of PHE were proposed. Flow through a periodic unit cell with four different geometries is simulated numerically to characterize the pressure drop, heat transfer coefficients, and entropy generation rate. The numerical results show good consistency with the existing experimental data. Results show that the flow in capsule-type plate can be divided into recirculation zone and high-velocity zone. The staggered capsule structure and the spherical dimple shape generate more secondary and impinging flows, which provide higher Nusselt number and friction factor. The maximum Nusselt number area changed from the upwind region of capsule to the vicinity of dimple region because of the downwash effect and the fluid impact effect. The Nusselt number is enhanced by 19%–46%, and the friction factor is 1.21–2.9 times to that of the primary capsule-type plate. In addition, Entropy analysis illustrates that the maximum reduction in the dimensionless entropy generation rate is 43.6%.

The entropy generation analysis and optimization of a water/silver nanofluid flow inside a photovoltaic thermal collector considering plain, ribbed, and porous-ribbed absorber tubes

BackgroundThe application of three (a) plain, (b) ribbed and (c) porous-ribbed absorber tube in a PVT solar collector was numerically investigated from the second law of thermodynamic points of view. MethodsThe 3-D laminar forced convection numerical analysis and optimization were performed for Res of 500–2000 and considering water/silver NF with the nanoparticle concentration ratios of 0–2%. Significant findingsThe results showed that the lowest thermal entropy generation rate (S˙th) is associated with the porous-ribbed configuration which is nearly 323% (or 253%) and 1211% (or 1059%) lower as compared to the plain (or ribbed) absorber tube. The moderate frictional entropy generation rate (S˙fr) was obtained for the porous-ribbed configuration which was 23.45% higher and 14.50% lower than that for the plain and ribbed tubes, respectively. The thermal exergy efficiency for the PVT with the porous-ribbed tube was nearly 50% and 46% higher than that with the plain and ribbed absorber tubes, respectively. However, the electrical exergy efficiency of the PVT with the porous-ribbed tube were superior to the ribbed and plain tubes only at low Res of 500 and 1000, while a reverse trend was obtained for the higher Res.

Entropy Generation Optimization in Couple Stress Fluid Flow with Variable Viscosity and Aligned Magnetic Field

This study explores the influence of an inclined magnetic field and variable viscosity on the entropy generation in steady flow of a couple stress fluid in an inclined channel. The walls of the channel are stationary and non-isothermal. The fluid flow is driven due to pressure gradient and gravitational force. Reynold’s model for temperature-dependent viscosity was used. The dimensionless, non-linear coupled equations of momentum and energy was solved, and we obtained an analytical solution for the velocity and temperature fields. The entropy generation and Bejan number were evaluated. The variation of pertinent parameters on flow quantities was discussed graphically. The rate of volume flow, skin friction coefficient, and Nusselt number at the surfaces of the channel were calculated and their variations were discussed through surface graphs. From the results, it is noticed that the entropy generation rate can be minimized by increasing the magnetic field and the temperature difference parameters. The findings of the current study in some special cases are in precise agreement with the previous investigation.

Entropy generation optimization in an unsteady hybrid nanofluid flow between two rotating disks: a numerical bioconvection model

In the context of bioconvection, bacteria are swimming microorganisms. Actually, a microorganism’s species is related to a focused swimming cell in the convection model. Unsteady chemically reactive (Water–Copper ()–Ferrous Oxide ()) hybrid nanofluid dynamics between two stretchable rotating disks at varied Lorentz force and viscous dissipation are unknown when the suspension of gyrotactic micro-organisms is taken into account. The paper’s novelty is addressing this gap, which is to examine the impact of chemical reactions on the unsteady bioconvective hybrid nanofluid flow between two stretchable rotating disks with viscous dissipation and the magnetic field. The use of Von-Karman similarity transformations allows for the conversion of governing equations into nonlinear ordinary differential equations. Based on the combination of Runge–Kutta fourth order and shooting methods, the final equations are calculated. A major finding of this study is Reynolds number escalates both axial and radial velocities but decreases the tangential velocity. The temperature increases with the rise in both Eckert number and heat source parameters. The concentration decreases with the rise in Schmidt number and chemical reaction parameter.

Matrixed modeling method and entropy generation minimization analysis of heat supply system based on standard thermal resistance

AbstractComplex implicit expressions and many intermediate parameters are not conducive to the application of entropy generation optimization to the performance of thermal and energy systems from component and system perspectives. In this paper, we derived matrix heat transport equations of three primary heat exchanger networks according to the heat current method. Based on the matrix equations, we established the matrixed model of a typical heat supply system and obtained the corresponding matrix equation reflecting the power topology structure of the system. Moreover, we derived and reconstructed a single heat exchanger's entropy generation rate expression based on the standard thermal resistance, which was only related to inlet temperatures, structural parameters, and operating parameters. The total system entropy generation rate was then derived and minimized by the Lagrange multiplier method. The optimization results provided the optimal distribution of the mass flow rate of each fluid. Besides, the influence of the heat transfer rate and outer loop inlet temperature on the optimization results revealed that local equipment parameters and conditions could affect the system's minimum entropy generation. The total entropy generation rate decreases by 17.5% when the outer loop inlet temperature was increased from 274 to 280 K. In conclusion, the matrixed modeling and entropy generation analysis are feasible for thermal system modeling and optimization.

Thermo-fluid characteristics and second law analysis of an inclined two-fluid system with variable surface roughness

The present numerical study focuses on the analysis of thermodynamic characteristics of an inclined two-fluid system (Al2O3-water and CuO-water nanofluids) having a heat conducting partition wall of variable surface roughness with constant geometric orientation. A further level of thermal control that results in an optimum system orientation for greater thermo-physical transport along with less entropy generation and thermal optimization is explored by examining the effect of system inclination. Based on the second law of thermodynamics, the quantitative results include the variation of average Nusselt number, average fluid temperature, average entropy generation, and average Bejan number for a wide range of Rayleigh number and inclination angle. Current study realizes that the mean quantitative properties of the system are significantly affected by the change of Rayleigh number and inclination angle, despite having a weak dependency on the partition roughness. The variation of average Bejan number with Rayleigh number assumes a reverse trend compared to the same for average Nusselt number and entropy generation and decreases continuously as the flow circulation strengthens. The rate of thermal transport is significantly regulated by the system orientation. Each Rayleigh number conforms to a critical angle of the system inclination for highest thermal transport and entropy generation.

Numerical investigation and optimization of natural convection and entropy generation of alumina/H2O nanofluid in a rectangular cavity in the presence of a magnetic field with artificial neural networks

The SIMPLE algorithm and the volume control technique are used to investigate the natural convection of alumina/H2O nanofluids (NFs) flow in a cavity. The cavity consists of two hot triangular blades on the bottom wall. The two sidewalls are insulated and the upper wall is at a low-temperature. The cavity can have different angles. Brownian nanoparticle motion is also considered to model their thermal conductivity and viscosity. Finally, the values ​​of Nusselt number (Nu), Bejan number (Be) entropy generation rate (Sgen) are estimated by changing the cavity angle (γ), the Hartmann number (Ha), and the Rayleigh number (Ra). It is found that an increment in the Ra enhances the amount of Nu and Sgen, but the amount of Be is reduced. An enhancement in the Ha does not effect on Sgen and Nu at low values of Ra, while for high amounts of Ra, Sgen and Nu are reduced. The maximum value of Sgen and Nu and the minimum amount of Be, which are 10.36, 5.21, and 0.34, respectively, occur when γ = 30°. Also, the minim values of Nu and Sgen occur for strong free convection in the horizontal and vertical cavity, respectively.