Marangoni convection in dissipative flow of nanofluid through porous space.

In various machinery engines, the engine oil is utilized as a lubricant. Heat transportation rate and to saving the energy dissipated due to higher temperature are the basic goals of all thermal systems. Thus, current work is mainly focused to develop a model for the Marangoni flow of nanofluids (NFs) with viscous dissipation. The considered NFs are made of nanoparticles (NPs) i.e. [Formula: see text] and base fluid (BF) as Engine Oil (EO). Darcy Forchheimer (DF) law which leads to porous medium is implemented in the model to investigate the variations of NF velocity and temperature. The governing flow expressions are simplified through similarity variables. The obtained expressions are solved numerically via an effective technique known as the NDSolve algorithm. The consequences of pertinent variables on temperature, velocity and Nusselt number are designed through tables and graphs. The obtained results reveal that velocity rises for higher Marangoni number, Darcy Forchheimer (DF) parameter whereas it shows decaying behavior against nanoparticles volume fraction.

Preventive Effect of Nuciferine on H2O2-Induced Fibroblast Senescence and Pro-Inflammatory Cytokine Gene Expression.

Human dermal fibroblasts play an important role in skin homeostasis by producing and degrading extracellular matrix components. They have more replicative senescence when exposed to environmental and oxidative insults, resulting in human skin aging. However, this phenomenon can be mitigated by antioxidant phytochemicals. The aim of the present study was to investigate the potential of nuciferine (an alkaloid from Nelumbo nucifera leaf) in preventing stress-induced fibroblast senescence by using a hydrogen-peroxide (H2O2)-induced senescence model. We found that H2O2 treatment resulted in a significant increase in senescence-associated ß-galactosidase (SA-ß-gal)-positive cells. Nuciferine-treated cells, however, showed a reduction in senescent phenotype. Furthermore, we observed the key molecular markers including the senescence-associated secretory phenotype (SASP) and cell cycle regulators. The mRNA levels of CXCL1, CXCL2, IL-6, and IL-8 (pro-inflammatory cytokines) reduced significantly in nuciferine-treated cells. The extracellular IL-6 and IL-8 levels were also decreased in treated cells, whereas the key cell cycle regulators (p16 and p21) were markedly affected by nuciferine at the highest concentration. The results of the present study clearly show that the preventive activity of nuciferine against H2O2-induced senescence in dermal fibroblasts is fundamental and promising for further applications in anti-aging product research and development.

A Higher-Order Galerkin Time Discretization and Numerical Comparisons for Two Models of HIV Infection.

Human immunodeficiency virus (HIV) infection affects the immune system, particularly white blood cells known as CD4+ T-cells. HIV destroys CD4+ T-cells and significantly reduces a human's resistance to viral infectious diseases as well as severe bacterial infections, which can lead to certain illnesses. The HIV framework is defined as a system of nonlinear first-order ordinary differential equations, and the innovative Galerkin technique is used to approximate the solutions of the model. To validate the findings, solve the model employing the Runge-Kutta (RK) technique of order four. The findings of the suggested techniques are compared with the results obtained from conventional schemes such as MuHPM, MVIM, and HPM that exist in the literature. Furthermore, the simulations are performed with different time step sizes, and the accuracy is measured at various time intervals. The numerical computations clearly demonstrate that the Galerkin scheme, in contrast to the Runge-Kutta scheme, provides incredibly precise solutions at relatively large time step sizes. A comparison of the solutions reveals that the obtained results through the Galerkin scheme are in fairly good agreement with the RK4 scheme in a given time interval as compared to other conventional schemes. Moreover, having performed various numerical tests for assessing the efficiency and computational cost (in terms of time) of the suggested schemes, it is observed that the Galerkin scheme is noticeably slower than the Runge-Kutta scheme. On the other hand, this work is also concerned with the path tracking and damped oscillatory behaviour of the model with a variable supply rate for the generation of new CD4+ T-cells (based on viral load concentration) and the HIV infection incidence rate. Additionally, we investigate the influence of various physical characteristics by varying their values and analysing them using graphs. The investigations indicate that the lateral system ensured more accurate predictions than the previous model.

A stochastic numerical approach for a class of singular singularly perturbed system.

In the present study, a neuro-evolutionary scheme is presented for solving a class of singular singularly perturbed boundary value problems (SSP-BVPs) by manipulating the strength of feed-forward artificial neural networks (ANNs), global search particle swarm optimization (PSO) and local search interior-point algorithm (IPA), i.e., ANNs-PSO-IPA. An error-based fitness function is designed using the differential form of the SSP-BVPs and its boundary conditions. The optimization of this fitness function is performed by using the computing capabilities of ANNs-PSO-IPA. Four cases of two SSP systems are tested to confirm the performance of the suggested ANNs-PSO-IPA. The correctness of the scheme is observed by using the comparison of the proposed and the exact solutions. The performance indices through different statistical operators are also provided to solve the SSP-BVPs using the proposed ANNs-PSO-IPA. Moreover, the reliability of the scheme is observed by taking hundred independent executions and different statistical performances have been provided for solving the SSP-BVPs to check the convergence, robustness and accuracy.

Mixed Convection Nanofluid Flow with Heat Source and Chemical Reaction over an Inclined Irregular Surface.

Two-dimensional mixed convection radiative nanofluid flow along with the non-Darcy permeable medium across a wavy inclined surface are observed in the present analysis. The transformation of the plane surface from the wavy irregular surface is executed via coordinate alteration. The fluid flow has been evaluated under the outcomes of heat source, thermal radiation, and chemical reaction rate. The nonlinear system of partial differential equations is simplified into a class of dimensionless set of ordinary differential equations (ODEs) through a similarity framework, where the obtained set of ODEs are further determined by employing the computational technique parametric continuation method (PCM) via MATLAB software. The comparative assessment of the current outcomes with the earlier existing literature studies confirmed that the present findings are quite reliable, and the PCM technique is satisfactory. The effect of appropriate dimensionless flow constraints is studied versus energy, mass, and velocity profiles and listed in the form of tables and figures. It is perceived that the inclination angle and wavy surface assist to improve the flow velocity by lowering the concentration and temperature. The velocity profile enhances with the variation of the inclination angle of the wavy surface, non-Darcian term, and wavy surface term. Furthermore, the rising value of Brownian motion and thermophoresis effect diminishes the heat-transfer rate.

Theoretical investigation of hybrid nanomaterials transient flow through variable feature of Darcy-Forchheimer space with exponential heat source and slip condition.

Nanomaterials have achieved remarkable importance in cooling small electronic gadgets like akin and microchips devices. The role of nanoparticles is essential in various aspects, especially in biomedical engineering. Thus hybrid nanomaterials is introduced to strengthen the heat exchangers' performance. In view of the above practical and existing applications of nanomaterials. Our aim is to examine the consequences of Darcy-Forchheimer's radiative and Hall current flow of nanomaterials over a rotating porous disk with variable characteristics. Stretching disk accounting for the slip condition. Nanoparticles ZnO and CoF2O4 are dispersed in based fluid water. The present model is utilized for thermo-physical attributes of hybrid nanomaterials with the impact of shape factor. Transformations convert the modeled PDEs into ODEs. The obtained highly non-linear system is tackled numerically by the NDSolve technique through the software Mathematica. The outcomes of significant variables against different profiles are executed and elaborated in detail. Obtained results show that both nano and hybrid nanofluid radial velocity have reverse behavior against variable porosity and permeability parameters, whereas it decays for larger Forchheimer numbers. Further, it is worthy to point out that, hybrid nanophase has a higher impact on distinct profiles when compared with nano and common liquid phases.

Numerical Approach toward Ternary Hybrid Nanofluid Flow Using Variable Diffusion and Non-Fourier's Concept.

In the current study, the pseudoplastic model is used to analyze the mass and energy transmission through trihybrid nanofluid flow across a stretched permeable surface. The Darcy-Forchheimer relation is employed in the momentum equation to examine the influence of porosity. Energy and mass diffusion expressions are obtained by employing the double diffusion theories, which were proposed by Cattaneo and Christov and is broadly used by several researchers. The thermal efficiency of the trihybrid nanocrystals is evaluated by integrating them with a pseudoplastic substrate. The study of titanium dioxide (TiO2), cobalt ferrite (CoFe2O4), and magnesium oxide (MgO) nanocomposite base hybrid nanofluids across a stretchable sheet is receiving considerable interest in innovation and research due to their extensive spectrum of applicability. For this reason, the phenomena are modeled in the form of a system of PDEs with the effects of a heat source, magnetic field, natural convection, and chemical reaction. Through resemblance substitutions, these are reduced to an ODE system. The resultant first-order differential equations are further processed using the computational approach PCM. For authenticity and reliability, the values are reviewed against the existing literature. The findings are displayed through figures. When compared to the simple nanofluid, the hybrid and trihybrid nanofluid have a greater tendency for fluid energy and velocity propagation rate. The velocity and heat transition rate enhance 11.73% by varying nanoparticles' values from 0.01 to 0.04, while the thermal conductivity of base fluid boosts with the addition of hybrid and trihybrid nanocomposites, up to 32% and 61%, respectively.

Numerical Study of Heat Transfer Enhancement within Confined Shell and Tube Latent Heat Thermal Storage Microsystem Using Hexagonal PCMs.

Thermophoresis represents one of the most common methods of directing micromachines. Enhancement of heat transfer rates are of economic interest for micromachine operation. This study aims to examine the heat transfer enhancement within the shell and tube latent heat thermal storage system (LHTSS) using PCMs (Phase Change Materials). The enthalpy-porosity approach is applied to formulate the melting situation and various shapes of inner heated fins are considered. The solution methodology is based on the Galerkin finite element analyses and wide ranges of the nanoparticle volume fraction are assumed, i.e., (0% ≤ φ ≤ 6%). The system entropy and the optimization of irreversibility are analyzed using the second law of the thermodynamics. The key outcomes revealed that the flow features, hexagonal entropy, and melting rate might be adjusted by varying the number of heated fins. Additionally, in case 4 where eight heated fins are considered, the highest results for the average liquid percentage are obtained.

Numerical Study of Lid-Driven Hybrid Nanofluid Flow in a Corrugated Porous Cavity in the Presence of Magnetic Field.

The lid-driven top wall's influence combined with the side walls' waviness map induce the mixed convection heat transfer, flow behavior, and entropy generation of a hybrid nanofluid (Fe3O4-MWCNT/water), a process analyzed through the present study. The working fluid occupies a permeable cubic chamber and is subjected to a magnetic field. The governing equations are solved by employing the GFEM method. The results show that the magnetic force significantly affects the working fluid's thermal and flow behavior, where the magnetic force's perpendicular direction remarkably improves the thermal distribution at Re = 500. Also, increasing Ha and decreasing Re drops both the irreversibility and the heat transfer rate. In addition, the highest undulation number on the wavy-sided walls gives the best heat transfer rate and the highest irreversibility.

Entropy Generation in 2D Lid-Driven Porous Container with the Presence of Obstacles of Different Shapes and under the Influences of Buoyancy and Lorentz Forces.

This paper includes a numerical investigation of a hybrid fluid containing 4% of Al2O3-Cu nanoparticles in a lid-driven container. The upper wall of the container has a high temperature and is movable. The lower wall is cool and wavy. An obstacle is set in the middle of the container for its effect on thermal activity. The medium is permeable to the fluid, and the entire system is immersed in a fixed-effect magnetic field. The digital simulation is achieved using the technique of Galerkin finite element (GFEM) which solves the differential equations. This investigation aims to know the pattern of heat transfer between the lateral walls and the lower wall of the container through the intervention of a set of conditions and criteria, namely: the strength of the magnetic field changes in the range of (Ha = 0 to 100); the chamber porosity varies in the range of (Da = 10-5 to 10-2); the strength of buoyancy force is varied according to the Grashof number (Gr = 102 to 104); the cross-section of the baffle includes the following shapes-elliptical, square, triangular and circular; the surface of the lower wall contains waves; and the number changes (N = 2 to 8). Through this research, it was concluded that the triangular shape of the baffle is the best in terms of thermal activity. Also, increasing the number of lower-wall waves reduces thermal activity. For example, the change in the shape of the obstacle from the elliptical to triangular raises the value of Nu number at a rate of 15.54% for Ha = 0, N = 8, and Gr = 104.

Solar energy optimization in solar-HVAC using Sutterby hybrid nanofluid with Smoluchowski temperature conditions: a solar thermal application.

In solar heating, ventilation, and air conditioning (HVAC), communications are designed to create new 3D mathematical models that address the flow of rotating Sutterby hybrid nanofluids exposed to slippery and expandable seats. The heat transmission investigation included effects such as copper and graphene oxide nanoparticles, as well as thermal radiative fluxing. The activation energy effect was used to investigate mass transfer with fluid concentration. The boundary constraints utilized were Maxwell speed and Smoluchowksi temperature slippage. With the utilization of fitting changes, partial differential equations (PDEs) for impetus, energy, and concentricity can be decreased to ordinary differential equations (ODEs). To address dimensionless ODEs, MATLAB's Keller box numerical technique was employed. Graphene oxide Copper/engine oil (GO-Cu/EO) is taken into consideration to address the performance analysis of the current study. Physical attributes, for example, surface drag coefficient, heat move, and mass exchange are mathematically processed and shown as tables and figures when numerous diverse factors are varied. The temperature field is enhanced by an increase in the volume fraction of copper and graphene oxide nanoparticles, while the mass fraction field is enhanced by an increase in activation energy.

Numerical Study of 3D MHD Mixed Convection and Entropy Generation in Trapezoidal Porous Enclosure Filled with a Hybrid Nanofluid: Effect of Zigzag Wall and Spinning Inner Cylinder.

A numerical study was performed to analyze the impact of the combination of several factors on heat transfer rate, flow behavior, and entropy generation in a hybrid nanofluid occupying a porous trapezoid enclosure containing a rotating inner tube. The governing equations were discretized and solved using the Finite Element Method using Comsol multiphysics. The effects of the Darcy and Hartman number, nanoparticle volume fraction (from 0 to 6%), the utilization of various zigzag patterns of the hot wall, and the rotation speed of the inner tube (Ω = 100. 250 and 500) are illustrated and discussed in this work. The outputs reveal that flow intensity has an inverse relationship with Hartman number and a direct relationship with the Darcy number and the velocity of the inner tube, especially at high numbers of undulations of the zigzag hot wall (N = 4); also, intensification of heat transfer occurs with increasing nanoparticle volume fraction, Darcy number and velocity of the inner tube. In addition, entropy generation is strongly affected by the mentioned factors, where increasing the nanoparticle concentration augments the thermal entropy generation and reduces the friction entropy generation; furthermore, the same influence can be obtained by increasing the Hartman number or decreasing the Darcy number. However, the lowest entropy generation was found for the case of Ø = 0, Ha = 0 and Da = 0.01.

Irreversibility Interpretation and MHD Mixed Convection of Hybrid Nanofluids in a 3D Heated Lid-Driven Chamber.

This paper presents a numerical simulation of a magneto-convection flow in a 3D chamber. The room has a very specific permeability and a zigzag bottom wall. The fluid used in this study is Al2O3-Cu/water with 4% nanoparticles. The Galerkin finite element technique (GFEM) was developed to solve the main partial equations. The hybrid nanofluid inside the container is subjected to the horizontal motion of the upper wall, an external magnetic field, and a thermal buoyancy force. The present numerical methodology is validated by previous data. The goal of this investigation was to understand and determine the percentage of heat energy transferred between the nanofluid and the bottom wall of the container under the influence of a set of criteria, namely: the movement speed of the upper wall of the cavity (Re = 1 to 500), the amount of permeability (Da = 10-5 to 10-2), the intensity of the external magnetic field (Ha = 0 to 100), the number of zigzags of the lower wall (N = 1 to 4), and the value of thermal buoyancy when the force is constant (Gr = 1000). The contours of the total entropy generation, isotherm, and streamline are represented in order to explain the fluid motion and thermal pattern. It was found that the heat transfer is significant when (N = 4), where the natural convection is dominant and (N = 2), and the forced convection is predominant.

Heat transfer analysis of Cu and Al2O3 dispersed in ethylene glycol as a base fluid over a stretchable permeable sheet of MHD thin-film flow.

The process of thin films is commonly utilized to improve the surface characteristics of materials. A thin film helps to improve the absorption, depreciation, flexibility, lighting, transport, and electromagnetic efficiency of a bulk material medium. Thin-film treatment can be especially helpful in nanotechnology. As a result, the current study investigates the computational process of heat relocation analysis in a thin-film MHD flow embedded in hybrid nanoparticles, which combines the spherical copper and alumina dispersed in ethylene glycol as the conventional heat transfer Newtonian fluid model over a stretching sheet. Important elements such as thermophoresis and Brownian movement are used to explain the characteristics of heat and mass transfer analysis. Nonlinear higher differential equations (ODEs) were attained by transforming partial differential equations (PDEs) into governing equations when implementing the similarity transformation technique. The resulting nonlinear ODEs have been utilized by using the homotopy analysis method (HAM). The natures of the thin-film flow and heat transfer through the various values of the pertinent parameters: unsteadiness, nanoparticle volume fraction, thin-film thickness, magnetic interaction, and intensity suction/injection are deliberated. The approximate consequences for flow rate and temperature distributions and physical quantities in terms of local skin friction and Nusselt number were obtained and analyzed via graphs and tables. As a consequence, the suction has a more prodigious effect on the hybrid nanofluid than on the injection fluid for all the investigated parameters. It is worth acknowledging that the existence of the nanoparticles and MHD in the viscous hybrid nanofluid tends to enhance the temperature profile but decays the particle movement in the thin-film flow. It is perceived that the velocity and temperature fields decline with increasing unsteadiness, thin-film thickness, and suction/injection parameters. The novel part of the present work is to investigate the hybrid nanofluid including Cu-Al2O3 dispersed in Ethylene glycol as a base fluid in the presence of a magnetic field, which has not been investigated yet. So, in limiting cases the present work is validated with published work and found in excellent agreement as shown in Table 3.

An advanced computing scheme for the numerical investigations of an infection-based fractional-order nonlinear prey-predator system.

The purpose of this study is to present the numerical investigations of an infection-based fractional-order nonlinear prey-predator system (FONPPS) using the stochastic procedures of the scaled conjugate gradient (SCG) along with the artificial neuron networks (ANNs), i.e., SCGNNs. The infection FONPPS is classified into three dynamics, susceptible density, infected prey, and predator population density. Three cases based on the fractional-order derivative have been numerically tested to solve the nonlinear infection-based disease. The data proportions are applied 75%, 10%, and 15% for training, validation, and testing to solve the infection FONPPS. The numerical representations are obtained through the stochastic SCGNNs to solve the infection FONPPS, and the Adams-Bashforth-Moulton scheme is implemented to compare the results. The infection FONPPS is numerically treated using the stochastic SCGNNs procedures to reduce the mean square error (MSE). To check the validity, consistency, exactness, competence, and capability of the proposed stochastic SCGNNs, the numerical performances using the error histograms (EHs), correlation, MSE, regression, and state transitions (STs) are also performed.