Layer Approximation Research Articles

Mechanical regulation strategy for heterogeneous piezoelectric semiconductor thermoelectric structure based on energy conversion

The piezoelectric properties inherent in piezoelectric semiconductors facilitate the manipulation of charge carrier redistribution, enabling the fabrication of electronic devices with adjustable characteristics. However, despite this capability, our understanding of the energy conversion and transfer mechanisms within such devices remains limited. By discarding the assumption of low injection and the approximation of depletion layer, a nonlinear model was developed on piezoelectric semiconductor thermoelectric structure (PS-TES), considering the penetration of hot electrons and regulation of mechanical loadings. The presented model reveals that the input electric energy is partitioned, with a portion being converted into electric potential energy stored (EPES) in non-equilibrium carriers and another portion being the energy dissipation (ED) due to the electrothermal action. Furthermore, from an energy conservation standpoint, a interesting competitive phenomenon between electric potential energy conversion and energy dissipation is obtained. The power of external electric energy input and internal electric energy conversion can be manipulated via mechanical loadings, thereby adjusting the energy conversion process of PS-TES. Finally, we found that the compressive loadings can increase EPES and reduce ED, thereby optimizing the cooling effect at cold end. While tensile loadings can reduce EPES and increase ED, thus causing the PS-TES to locally heat up and produce a heating effect. This study potentially offers a means to switch the performance of TES and provides fresh insights into energy conversion processes within piezoelectric semiconductors.

Investigation of convective heat transport in a Carreau hybrid nanofluid between two stretchable rotatory disks

Abstract Hybrid nanofluids (HNFs) have outstanding energy transfer capabilities that are comparable to mono-nanofluids. Materials had appliances in obvious fields such as heat generation, micropower generation, and solar collectors. The objective of this study is to investigate the new aspects of convective heat transfer in an electrically conducting Carreau HNF situated between two parallel discs. In addition to the presumed stretchability and rotation of the discs, physical phenomena like nonlinear radiation, viscous dissipation, Joule dissipation, and heat generation and absorption are considered. The Cu and TiO2 nanoparticles dispersed in engine oil to understand the intricate phenomenon of hybridization. The Tiwari and Das nanofluid model is employed to model the governing partial differential equations (PDEs) and then simplified using boundary layer approximation. The suitable transformations of similarity variables are defined and implemented to change the set of formulated PDEs into ordinary differential equations. The reduced system is solved semi-analytically by the homotopy analysis method. The influences of involving physical parameters on the velocity and temperature are plotted with the help of graphical figures. This study brings forth a significant contribution by uncovering novel flow features that have previously remained unexplored. By addressing a well-defined problem, our research provides valuable insights into the enhancement of thermal transport, with direct implications for diverse engineering devices such as solar collectors, heat exchangers, and microelectronics.

General-Kindred physics-informed neural network to the solutions of singularly perturbed differential equations

Physics-informed neural networks (PINNs) have become a promising research direction in the field of solving partial differential equations (PDEs). Dealing with singular perturbation problems continues to be a difficult challenge in the field of PINN. The solution of singular perturbation problems often exhibits sharp boundary layers and steep gradients, and traditional PINN cannot achieve approximation of boundary layers. In this manuscript, we propose the General-Kindred physics-informed neural network (GKPINN) for solving singular perturbation differential equations (SPDEs). This approach utilizes asymptotic analysis to acquire prior knowledge of the boundary layer from the equation and establishes a novel network to assist PINN in approximating the boundary layer. It is compared with traditional PINN by solving examples of one-dimensional, two-dimensional, and time-varying SPDE equations. The research findings underscore the exceptional performance of our novel approach, GKPINN, which delivers a remarkable enhancement in reducing the L2 error by two to four orders of magnitude compared to the established PINN methodology. This significant improvement is accompanied by a substantial acceleration in convergence rates, without compromising the high precision that is critical for our applications. Furthermore, GKPINN still performs well in extreme cases with perturbation parameters of 1×10−38, demonstrating its excellent generalization ability.

Heat transportation of 3D chemically reactive flow of Jeffrey nanofluid over a porous frame with variable thermal conductivity

Nanofluids with variable thermal conductivity can potentially bring about a transformative impact in various industries. They offer adaptive and efficient heat transfer solutions that can adjust to changing conditions and specific requirements. The insertion of nanoparticles into the base fluid significantly changes its properties, affecting thermal conductivity and viscosity. The primary objective of this paper is to analyze the heat transfer rate and three-dimensional bio-convective flow of a non-Newtonian Jeffrey nanofluid across a porous surface with variable thermal conductivity. The investigation also considers the impacts of thermophoresis, Brownian motion, and the Lorentz force. The combine impact of thermal radiation and motile microbes also incorporated in the current study. To model these phenomena, we employ the boundary layer approximation to derive a system of partial differential equations (PDEs). These PDEs are subsequently simplified into more manageable ordinary differential equations (ODEs) using the similarity variables. The numerical analysis is performed via the finite difference approach, which consists of a three-stage Lobatto scheme using MATLAB package. Additionally, important engineering parameters under different constraints-like skin friction, Nusselt number, and Sherwood number—are given in a thorough manner using tabular and graphical representations. The results of this study demonstrate significant enhancements in various aspects, including thermophoresis, Brownian motion, and thermal boundary layer thickness are demonstrated through graphically and in the form of tables. As the thermal radiation parameter increases, the temperature profile rises accordingly. This enhancement in the temperature profile is directly attributable to the higher value of the radiation parameter, which results in a physical increase in temperature. These improvements are attributed to a reduction in viscous forces and an increase in the Brownian diffusion coefficient. This research advances the understanding of non-Newtonian thermally radiative flow with variable thermal conductivity, elucidating the complex behavior of such fluids and providing valuable insights for engineering applications.

Double-diffusive convection in flow of Carreau fluid with variable density inside converging and diverging channels of rectilinear walls

In this article, the effects of double-diffusive convection have been seen on the flow of Carreau fluid of variable density, maintained inside straight and converging (diverging) channels. Note that the channel walls exhibit variable porosity and undergo stretching or shrinking at non-uniform velocities. In the flow domain, we have taken into account the convective transport of both heat and species mass concentrations. The pseudo-similarity solutions of previous investigation for such type flows are not used here; however, a new set of similarity transformations has been formed, which reduced the governing system (PDEs) into an exact set of ordinary differential equations (ODEs), whereas the longstanding issues of semi-similarity solutions have been successfully resolved in this particular case and in general for all situations of Carreau fluid flow. In a nutshell, a unified mathematical approach has been devised in this paper. We strictly emphasized the simulation of flow of Carreau fluid and double diffusive convection in flow inside a channel with multiple dynamical behaviours and structures (both Jeffery Hammel and Poissuielle flow types) of walls. The boundary layer approximation and stream function assumptions have not been used in the study's execution. The shear thinning and shear thickening features of Carreau fluids with variable density cause them to exhibit lower axial velocity in the centre of a horizontal channel than Newtonian fluids due to variable wall configurations and complex flow conditions. By enhancing buoyancy driven convection, which promotes effective heat dispersion, increasing the solutal and thermal Grashof numbers (GrS=GrT>0) lowers the temperature field. It has been found that in channel with diverging walls (a1=2.0), increasing the modified Reynolds numbers (σ1,σ2>0) increases concentration profiles, i.e. ϕ(η), while decreasing them in channel with rectilinear walls (a1=0.0).

Scrutiny of pseudoplastic nanofluid flow under the influence of magnetic hydrodynamics with chemical reaction across the cylinder with slip boundary condition

Buoyantly induced flows possess diversified utilizations in numerous engineering processes for instance, reactor cooling through passive strategy, LED lights, pipes manufacturing, ship funnel and many more. Galvanized sheets sticked to form a hollow cylinder is used for fast cooling in naval ship and chimney of steam power plant. In view of such mesmerizing significance of flow and thermal attributes of fluid over vertical cylinder, current effort is articulated. For this purpose, Williamson fluid model is accounted and nanoparticles are also induced to envision advanced thermal features in the flow over vertically oriented cylinder. Physical effectiveness of magnetic field implications and chemical reactive species are entertained to notice change in hydrothermal and mass fields. Slip boundary constraint along with stagnant flow at the surface of cylinder is considered to inspect behavior in free stream region. The fundamental governing equations of problem are attained in the sense of PDEs by utilizing the concept of boundary layer approximation and converted into coupled nonlinear ODEs by substituting specific similar variables. Numerically the resulting ODEs are resolved by making the use of bvp4c built in MATLAB routine, the outcomes are attained and arranged in graphical and tabular manner. The influence of pertinent flow parameters such as (0.1 ≤ We ≤ 1.0), (1.0 ≤ M ≤ 3.0), (1.0 ≤ Pr ≤ 11), thermophoresis parameter (0.5 ≤ Tp ≤ 4.5), (1.0 ≤ Bp ≤ 5.0), (0.05 ≤ Nr ≤ 0.7), and (0.5 ≤ Kc ≤ 5.0) are examined on the momentum, thermal and concentration distributions. It is manifested that the velocity distribution depreciates by uplifting magnetic field strength. Increment in magnitude of wall drag and convective heat transfer is perceived by enhancing Prandtl number. It is inferred that friction coefficient in absolute sense and heat flux coefficient tends to exceed against elevation in (We). From comprehensive analysis, declination in velocity and thermal field is depicted versus Reynold number whereas, contrary aspects are visualized in concentration. Enhancement in the value of surface drag and thermal flux is revealed versus (Re).

Thin layer axion dynamo

We study interacting classical magnetic and pseudoscalar fields in frames of the axion electrodynamics. A large scale pseudoscalar field can be the coherent superposition of axions or axion like particles. We consider the evolution of these fields inside a spherical clump. Decomposing the magnetic field into the poloidal and toroidal components, we take into account their symmetry properties. Within a spherical clump, we use a thin layer approximation in the induction and Klein–Gordon equations, where the dependence of the fields on the latitude is accounted for. Then, we derive the dynamo equations in the low mode approximation. The nonlinear evolution equations for the harmonics of the magnetic and pseudoscalar fields are solved numerically. As an application, we consider a dense axion star embedded in solar plasma. The behavior of the harmonics and their typical oscillations frequencies are obtained. We suggest that such small size axionic objects, containing oscillating magnetic fields, can cause electromagnetic flashes, recently observed in the solar corona, contributing to the corona heating.

Self-chemophoresis in the thin diffuse interface approximation

Self-chemophoresis is an appealing and quite successful interpretation of the motility exhibited by certain chemically active colloidal particles suspended in a solution of their ‘fuel’: the particle has a phoretic response to self-generated, rather than externally imposed, inhomogeneities in the chemical composition of the solution. The postulated mechanism of chemophoresis is the interaction of the particle (via an adsorption potential) with the chemical inhomogeneities in the surrounding medium. When the range of this interaction is much smaller than any other relevant scale in the system, the (translational and rotational) phoretic velocities can be described in terms of a phoretic coefficient and a slip fluid velocity at the surface of the particle. Using the case of a spherical particle as a simple and physically insightful example, here we exploit an integral representation of the rigid-body motion to critically re-examine this framework. The systematic analysis highlights two steps in the approximation: first the thin–layer approximation (very large particle size), and subsequently a lubrication approximation (slow variation of the adsorption potential along the tangential direction). We also discuss how these approximations could be relaxed and the effect of this on the particle's motion.

Exponential time difference methods with spatial exponential approximations for solving boundary layer problems

AbstractIn this work, an efficient and stable exponential time difference method is presented for solving boundary layer problems. By combining exponential time difference schemes with spatial direct discontinuous Galerkin discretization based on exponential boundary layer approximations, the proposed algorithm not only may admit large time step sizes but also could provide good spatial approximations even if on rather coarse spatial grids in the boundary layer. Some energy stabilities of the numerical scheme are rigorously derived. Numerical examples illustrate the accuracy, stability and efficiency of the algorithm.

Stagnation point radiative flow with Cattaneo-Christov theory and heat generation

Heat generation and magnetohydrodynamics for flow of Burgers liquid. Stagnation point flow towards stretched wall is considered. Radiation aspect is nonlinear. Cattaneo-Christov theory and boundary layer approximations are utilized. Related differential systems are formulated. Computations by Optimal homotopy analysis method (OHAM) are implemented. Total residual error is arranged. Graphical illustrations lead to the impacts of sundry parameters. Important points have been concluded. Higher Deborah number lead to velocity enhancement. Decrease in velocity occurs for magnetic field whereas reverse trend witnessed regarding thermal field. Temperature upsurges for higher radiation and heat generation variables. Higher radiation results in Nusselt number enhancement. Mass transport rate enhancement versus Schmidt number is observed. Reduction of thermal distribution occurs for thermal relaxation time.

Neural network algorithms of a curved riga sensor in a ternary hybrid nanofluid with chemical reaction and Arrhenius kinetics

To improve the thermal management systems in industrial operations, there is a need for the prediction and complexity of advanced fluid motion across various physical conditions on different geometries. Further, ternary nanofluid flow across curved Riga surfaces plays a significant role in thermal management systems, chemical industries, thermal management systems, biomedical, environmental engineering, and more. Based on the above importance the current study focuses artificial neural network (ANN) model on the ternary nanofluid flow over a curved Riga surface in the presence of chemical reaction and activation energy. Proper assumptions and boundary layer approximation were used to develop the model. Using appropriate similarity variables, the governing equations are further simplified to ordinary differential equations (ODEs). Runge Kutta Fehlberg's 4th-5th order and shooting process are applied to solve the simplified equations. The primary objective is to improve the construction and optimization of thermal administration systems and other manufacturing procedures by gaining a deeper knowledge of the fluid motion and characteristics of heat transfer involved. Graphs are used to provide additional context for the important dimensionless constraints. The obtained data was utilized to train the ANN model, which was then verified towards numerical values of important engineering coefficients. The results reveal that the addition of solid volume fraction will enhance the thermal profile while declining the concentration profile. The reaction rate parameter will decline the concentration, and a reverse trend is seen for the activation energy parameter. The constructed model exhibits an outstanding degree of precision throughout the procedure, spanning all phases of the research.

Study and Application of Fine Dissection Methods for Inter-river Sands in Large Shallow River-controlled Delta Plains

Applying the data of coring wells and logging curves of dense well network, identifying the sedimentary sands of different river systems and contemporaneous periods with the methods of standard layer approximation control and comparison of reference layer combinations, establishing a set of logging phase models of inter-river sands, and using the models as a guideline for micro-phase identification, we have studied the distribution and combination characteristics of the micro-phase sands of the inter-river sand bodies, as well as the type of connectivity with the sand bodies of the river and the relationship, and clarified the distribution characteristics and residual oil distribution of the sand bodies of the inter-river sands. The characteristics of different types of sand body movement and residual oil distribution were clarified, effective dredging methods were proposed, and measures such as oil testing and fracturing were taken, which played an important role in guiding the adjustment and dredging of oil fields in the late stage of high water content.

Oscillatory onset of rotating thermal convection subject to spatially varying magnetic fields and stable stratification

Convective fluid motions in deep planetary cores induce spatially and temporally varying magnetic fields observable as secular variation. Oscillatory instabilities occurring as onset modes in rapidly rotating thermal convection influenced by heterogeneous magnetic fields and stratification, investigated in this study, can be potentially linked to such observations. A plane layer approximation to near-polar and near-equatorial regions of the Earth's outer core is considered. In addition to penetrative convection and flow suppression effects, the simultaneous interaction of convective instabilities with asymmetrical magnetic fields and stable stratification is the focus of this study. The fundamental modes of magnetoconvection onset are preserved even under stable stratification, although the convection threshold is lowered irrespective of the parameter regime. The axial invariance of rapidly rotating columnar convection loses its midplane symmetry with intense localization of kinetic energy in the unstably stratified regions. The parameter regimes supporting the onset of the magnetically modified viscous oscillatory (mVO) modes are further extended toward Earthlike conditions such as high thermal conductivity (low Prandlt number, Pr) and magnetic dissipation (low Roberts number, q). Moreover, compared to fully unstable stratification, partial stable stratification enhances the range of imposed magnetic field length scale (δ) over which the onset of mVO modes is favored. The critical field length scale (δ⋆), above which the onset regime of the mVO modes is bounded by a minimum q, is determined. Irrespective of the rotation rate, below δ=δ⋆, the onset of the mVO mode is supported for asymptotically small q for Pr values close to the Earth's outer core.

Numerical Analysis of MHD Casson Fluid Flow over a Stretching Surface with Chemical Reaction and Variable Thermal Conductivity

The motivation of the current article is to explore the Numerical analysis of MHD Casson fluid flow over a Stretching surface. Three dimensional, non-linear of an incompressible fluid flow in the presence of chemical reaction and variable thermal conductivity is considered. The mathematical model effectively describes the current flow analysis. The Governing equations are simplified with the help of boundary layer approximations. Non-linear coupled equations for momentum, energy and mass transfer are tackled with MATLAB bvp4c. The behavior of various non-dimensional parameters which are involved in the derived set of equations are described and explained in detailed through graph.

Non-Fourier computations of heat and mass transport in nanoscale solid-fluid interactions using the Galerkin finite element method

PurposeTo improve the thermal performance of base fluid, nanoparticles of three types are dispersed in the base fluid. A novel theory of non-Fourier heat transfer is used for design and development of models. The thermal performance of sample fluids is compared to determine which types of combination of nanoparticles are the best for an optimized enhancement in thermal performance of fluids. This article aims to: (i) investigate the impact of nanoparticles on thermal performance; and (ii) implement the Galerkin finite element method (GFEM) to thermal problems.Design/methodology/approachThe mathematical models are developed using novel non-Fourier heat flux theory, conservation laws of computational fluid dynamics (CFD) and no-slip thermal boundary conditions. The models are approximated using thermal boundary layer approximations, and transformed models are solved numerically using GFEM. A grid-sensitivity test is performed. The accuracy, correction and stability of solutions is ensured. The numerical method adopted for the calculations is validated with published data. Quantities of engineering interest, i.e. wall shear stress, wall mass flow rate and wall heat flux, are calculated and examined versus emerging rheological parameters and thermal relaxation time.FindingsThe thermal relaxation time measures the ability of a fluid to restore its original thermal state, called thermal equilibrium and therefore, simulations have shown that the thermal relaxation time associated with a mono nanofluid has the most substantial effect on the temperature of fluid, whereas a ternary nanofluid has the smallest thermal relaxation time. A ternary nanofluid has a wider thermal boundary thickness in comparison with base and di- and mono nanofluids. The wall heat flux (in the case of the ternary nanofluids) has the most significant value compared with the wall shear stresses for the mono and hybrid nanofluids. The wall heat and mass fluxes have the highest values for the case of non-Fourier heat and mass diffusion compared to the case of Fourier heat and mass transfer.Originality/valueAn extensive literature review reveals that no study has considered thermal and concentration memory effects on transport mechanisms in fluids of cross-rheological liquid using novel theory of heat and mass [presented by Cattaneo (Cattaneo, 1958) and Christov (Christov, 2009)] so far. Moreover, the finite element method for coupled and nonlinear CFD problems has not been implemented so far. To the best of the authors’ knowledge for the first time, the dynamics of wall heat flow rate and mass flow rate under simultaneous effects of thermal and solute relaxation times, Ohmic dissipation and first-order chemical reactions are studied.

Sensitivity Analysis of Electrochemical Double Layer Approximations on Electrokinetic Predictions: Case Study for CO Reduction on Copper

Sensitivity Analysis of Electrochemical Double Layer Approximations on Electrokinetic Predictions: Case Study for CO Reduction on Copper

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.

Compact Model Training by Low-Rank Projection With Energy Transfer.

Low-rankness plays an important role in traditional machine learning but is not so popular in deep learning. Most previous low-rank network compression methods compress networks by approximating pretrained models and retraining. However, the optimal solution in the Euclidean space may be quite different from the one with low-rank constraint. A well-pretrained model is not a good initialization for the model with low-rank constraints. Thus, the performance of a low-rank compressed network degrades significantly. Compared with other network compression methods such as pruning, low-rank methods attract less attention in recent years. In this article, we devise a new training method, low-rank projection with energy transfer (LRPET), that trains low-rank compressed networks from scratch and achieves competitive performance. We propose to alternately perform stochastic gradient descent training and projection of each weight matrix onto the corresponding low-rank manifold. Compared to retraining on the compact model, this enables full utilization of model capacity since solution space is relaxed back to Euclidean space after projection. The matrix energy (the sum of squares of singular values) reduction caused by projection is compensated by energy transfer. We uniformly transfer the energy of the pruned singular values to the remaining ones. We theoretically show that energy transfer eases the trend of gradient vanishing caused by projection. In modern networks, a batch normalization (BN) layer can be merged into the previous convolution layer for inference, thereby influencing the optimal low-rank approximation (LRA) of the previous layer. We propose BN rectification to cut off its effect on the optimal LRA, which further improves the performance. Comprehensive experiments on CIFAR-10 and ImageNet have justified that our method is superior to other low-rank compression methods and also outperforms recent state-of-the-art pruning methods. For object detection and semantic segmentation, our method still achieves good compression results. In addition, we combine LRPET with quantization and hashing methods and achieve even better compression than the original single method. We further apply it in Transformer-based models to demonstrate its transferability. Our code is available at https://github.com/BZQLin/LRPET.

Computational analysis of the bioconvective flow of Williamson–Sutterby fluid with microorganisms and activation energy subject to Cattaneo–Christov double-diffusion effects

This research aims to develop a mathematical model and outline the implications of the free convection flow within a non-Newtonian Williamson–Sutterby type nonfluid through a stretching surface placed horizontally with magnetic dipole effect. The present attempt establishes the influence of multiple factors, including double diffusion, and heat flux. Utilizing the Cattaneo–Christov heat mass flux model approximations, to shape the thermal and concentration balance equations, incorporating various generalized transport laws. Furthermore, the transportation mechanism incorporates Arrhenius activation energy and binary chemical reactions. The impact of bioconvection resulting from self-propelled microorganisms is incorporated into the fluidic model. A nonlinear set of partial differential equations (PDEs) are appropriately formulated, employing boundary layer approximations theory, to comprehensively describe the convective flow. The PDEs are converted to ordinary differential equations via similarity transformation, and then computationally computed via a well-structured RKF45 technique with a shooting algorithm. To validate the results, a comparison is made with published findings in limiting cases. It is observed that the velocity profiles exhibit an escalation in tandem with ascending values of the electric parameter and mixed convection. Conversely, the velocity diminishes with the augmentation of the magnetic factor, ferrohydrodynamic interaction parameter, porosity parameter, and Sutterby fluid parameter. Temperature profiles elevate in response to escalating values of the Eckert number, radiation parameter, and Brownian motion parameter while diminishing with the augmentation of the thermal relaxation constant, Prandtl number, and Sutterby fluid parameter. The concentration distribution exhibits an augmentation with the increasing magnitude of the thermophoresis parameter and activation energy while experiencing a reduction with the improvement in the behavior of Schmidt number and Brownian parameter. The ongoing investigation encompasses a wide spectrum of applications within the field of applied sciences, placing particular emphasis on thermal oil recovery, geothermal reservoirs, chemical engineering, and the cooling processes pertinent to nuclear reactors.

Computational framework for thermal transportation in radiative bio-convective micropolar nanomaterial flow over stretched sheet with entropy optimization

Entropy generation (EG) in bioconvective nanofluid flows is a phenomenon that occurs due to the presence of nanoparticles and microorganisms within fluid flows. EG leads to an increase in thermodynamic irreversibility within the system. Understanding and quantifying EG in nanofluid flows is essential to optimize heat transfer processes and design efficient systems. Current investigation aims to analyze the irreversibility of the magnetized bioconvective flow of non-Newtonian micropolar type nanofluid. Flow features are modeled considering flow by a Darcy Forchheimer permeable surface of a stretched sheet. Phenomenon of bioconvection in a micropolar fluid is considered to regulate the solid tiny particles. Magnetic field and permeability effects are accounted in momentum relation. Energy relation is constructed in the presence of Joule heating, internal fluid friction, and thermal radiation. Mass concentration equation is formulated by accounting Arrhenius kinetics and binary chemical reaction. Furthermore, the buoyancy effects of solid tiny particles are considered in thermal and concentration relations. Total entropy of the considered flow is modeled using the second thermodynamics law. System of dimensional equations representing the flow is obtained with the implementation of boundary layer approximations. The acquired system is altered into an ordinary one through transformations and then tackled by numerical scheme Runge-Kutta-Fehlberg method (RKF-45) in the Mathematica package. Behavior of velocity, thermal field, entropy production, mass concentration, motile density, and Bejan number versus sundry variables is investigated through plots. Skin friction, local heat, mass, and density rates are numerically examined. Thermal field upsurges and velocity field decays versus higher Hartmann number. Entropy generation improved versus higher Brinkman number, microorganisms diffusion variable, and temperature difference ratio variable.