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This work aims to examine the entropy production, heat transport, and dynamics of the unsteady thin film magnetohydrodynamic (MHD) flow of a nanofluid composed of alumina (Al2O3) and water. The fluid flow is seen to pass over an inclined sheet, taking into account the effects of buoyancy force, viscous dissipation, and joule heating. The system of partial differential equations (PDEs) is optimized under the boundary layer assumptions. Appropriate transformations are used to convert the governing partial differential equations (PDEs) and boundary conditions into dimensionless forms. Using MATLAB's bvp4c code and a local non-similarity technique with up to second-degree truncation, we can obtain the findings of the enhanced model. The effect of multi-shape Al2O3 nanoparticles on flow, heat, and entropy-generating features is also investigated after the calculated results have been successfully aligned with published data. Mixed convection, nanoparticle volume percent, inclination angle, magnetic field intensity, mass suction, Eckert number, and Biot number are only a few of the governing parameters whose effects are graphically shown for selected values. As a result, the local Nusselt number and skin friction coefficient may be calculated. The skin friction and Nusselt number profiles exhibit a decreasing trend as the values of nanoparticle volume fraction (ϕ) magnetic (M) and unsteadiness (A) increase toward mixed convection (δ). On the other hand, Nusselt number profile increases with increasing values of mass suction parameter (S) The profiles of entropy generation and Bejan number show an upsurge as the values of the magnetic parameter (M) and Brinkman number (Br) increase. Conversely, the entropy generation reduces with an increase in the temperature difference parameter (Ω) and Bejan number increases. [ABSTRACT FROM AUTHOR]

The slip flow of nanofluids has engaged potential applications in different engineering processes, including oil recovery, aerodynamics, microfluidic and chip devices, lubrication and tribology, and environmental engineering. Following such motivated applications in mind, the objective of the current analysis is to incorporate multiple slip effects in the flow of micropolar nanofluids due to a shrinking surface. The velocity, thermal, and concentration slip effects are endorsed to analyze the flow. Insights into heat transfer are subject to the radiative phenomenon. The stability analysis of the defined problem has been performed. The developed problem into a dimensionless form is solved with the help of the Keller box scheme. The accuracy of solution is confirmed with available research data. The implementation of the Keller box technique leads to multiple solutions. Physical justification of the problem is presented for each flow parameter. It is observed that dual solutions exist for specific numerical values of involved parameters for the shrinking flow problem. A reduction in fluid velocity is noticed for the velocity slip parameter. The micro-rotational profile declined due to the micro-rotation parameter. Furthermore, heat transfer enhances due to Brownian and thermophoresis parameters. [ABSTRACT FROM AUTHOR]

The steam condenser is a crucial component in power plants, playing a vital role in influencing the overall performance of steam power plants. This paper delves into a detailed assessment of the thermal aspects and evaluation of steam surface condensers. To conduct this rigorous evaluation, we meticulously crafted a three-dimensional (3D) model of a multi-tube single-pass counter-flow heat exchanger using ANSYS Design-Modeller. Within this model, a multiphase mixture model was harnessed to replicate the condensation process that takes place within the condenser. After the model's development, a series of computational fluid dynamics (CFD) simulations were expertly executed utilizing ANSYS Fluent Workbench. The simulations encompassed diverse cooling water flow rates and steam inlet velocities. Notably, two sets of CFD simulations were carried out: the initial set featured a velocity inlet in the condenser, while the second set involved CFD simulations with a pressure steam inlet. The findings derived from these simulations unveiled a noteworthy correlation between the condensation rate within the shell and both the rate of circulating water flow and the operational pressure of the condenser. Additionally, it was discerned that the condensation rate could be further influenced by the specific geometry of the condenser. In sum, this study concludes that optimizing the geometrical configuration and baffle arrangements holds promise for increasing the condensation rate and overall performance of steam condensers employed within steam power plants. [ABSTRACT FROM AUTHOR]

In this research work, we investigate the complex structure of soliton in the Fractional Kudryashov–Sinelshchikov Equation (FKSE) using conformable fractional derivatives. Our study involves the development of soliton solutions using the modified Extended Direct Algebraic Method (mEDAM). This approach involves a key variable transformation, which successfully transforms the model into a Nonlinear Ordinary Differential Equation (NODE). Following that, by using a series form solution, the NODE is turned into a system of algebraic equations, allowing us to construct soliton solutions methodically. The FKSE is the governing equation, allowing for heat transmission and viscosity effects while capturing the behaviour of pressure waves in liquid–gas bubble mixtures. The solutions we discover include generalised trigonometric, hyperbolic, and rational functions with kinks, singular kinks, multi-kinks, lumps, shocks, and periodic waves. We depict two-dimensional, three-dimensional, and contour graphs to aid comprehension. These newly created soliton solutions have far-reaching ramifications not just in mathematical physics, but also in a wide range of subjects such as optical fibre research, plasma physics, and a variety of applied sciences. [ABSTRACT FROM AUTHOR]

The numerical investigation of bioconvective nanofluid (NF) flow, which involves gyrotactic microbes and heat and mass transmission analysis above an inclined extending axisymmetric cylinder, is presented in this study. The study aims to investigate the bioconvection flow of nanofluid under the influence of heat sources/sinks. Through proper transformation, all partial differential equations are transformed into a non-linear ODE scheme. A new set of variables is presented in the directive to get the first-order convectional equations and then solved numerically using bvp4c MATLAB, embedded in the function. The proposed model is validated after calculating the error estimation and obtaining the residual error. The influence of various factors on the velocity, energy, concentration, and density of motile microorganisms is examined and studied. The analysis describes and addresses all physical measures of concentration such as Skin Friction (SF), Sherwood number, the density of motile microorganisms, and Nusselt number. To validate the present study, a comparison is conducted with previous studies, and excellent correspondence is found. In addition, the ND-Solve approach is utilized to confirm the bvp4c. The mathematical model is confirmed through error analysis. This study provides the platform for industrial applications such as cooling capacity polymers, heat exchange, and chemical production sectors. [ABSTRACT FROM AUTHOR]

Nonlinear thermal transport of non-Newtonian polymer flows is an increasingly important area in materials engineering. Motivated by new developments in this area which entail more refined and more mathematical frameworks, the present analysis investigates the boundary-layer approximation and heat transfer persuaded by a symmetrical cylindrical surface positioned horizontally. To simulate thermal relaxation impacts, the bioconvection Cross nanofluid flow Buongiorno model is deployed. The study examines the magnetic field effect applied to the nanofluid using the heat generated, as well as the melting phenomenon. The nonlinear effect of thermosolutal buoyant forces is incorporated into the proposed model. The novel mathematical equations include thermophoresis and Brownian diffusion effects. Via robust transformation techniques, the primitive resulting partial equations for momentum, energy, concentration, and motile living microorganisms are rendered into nonlinear ordinary equations with convective boundary postulates. An explicit and efficient numerical solver procedure in the Mathematica 11.0 programming platform is developed to engage the nonlinear equations. The effects of multiple governing parameters on dimensionless fluid profiles is examined using plotted visuals and tables. Finally, outcomes related to the surface drag force, heat, and mass transfer coefficients for different influential parameters are presented using 3D visuals. [ABSTRACT FROM AUTHOR]

In this article, we considered a 3D symmetric flow of a ternary hybrid nanofluid flow (THNF) past a nonlinear stretching surface. The effect of the thermal radiation is considered. The THNF nanofluid SiO 2 +Cu+MoS 2 /H 2 O is considered in this work, where the shapes of the particles are assumed as blade, flatlet, and cylindrical. The problem is formulated into a mathematical model. The modeled equations are then reduced into a simpler form with the help of suitable transformations. The modeled problem is then tackled with a new machine learning approach known as a hybrid cuckoo search-based artificial neural network (HCS-ANN). The results are presented in the form of figures and tables for various parameters. The impact of the volume fraction coefficients ϕ 1 , ϕ 2 , and ϕ 3 , and the radiation parameter is displayed through graphs and tables. The higher numbers of the radiation parameter (R d) and the cylinder-shaped nanoparticles, ϕ 3 , enhance the thermal profile. In each case, the residual error, error histogram, and fitness function for the optimization problem are presented. The results of the HCS-ANN are validated through mean square error and statistical graphs in the last section, where the accuracy of our implemented technique is proved. [ABSTRACT FROM AUTHOR]

This paper explores the numerical optimization of heat and mass transfer in the buoyancy-driven Al2O3-water nanofluid flow containing electrified Al2O3-nanoparticles adjacent to a symmetrically-vertical plane wall. The proposed model becomes a set of nonlinear problems through similarity transformations. The nonlinear problem is solved using the bvp4c method. The results of the proposed model concerning heat and mass transfer with nanoparticle electrification and buoyancy parameters are depicted in the Figures and Tables. It was revealed that the electrification of nanoparticles enhances the heat and mass transfer capabilities of the Al2O3 water nanoliquid. As a result, the electrification of nanoparticles could be an important mechanism to improve the transmission of heat and mass in the flow of Al2O3-water nanofluids. Furthermore, the numerical solutions of the nanofluid model of heat/mass transfer using the deep neural network (DNN) along with the procedure of Bayesian regularization scheme (BRS), DNN-BRS, was carried out. The DNN process is provided by taking eight and ten neurons in the first and second hidden layers along with the log-sigmoid function. [ABSTRACT FROM AUTHOR]