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In the current work, in the presence of a heat source and temperature gradients, the onset of triple-diffusive convective stability is studied for a fluid, and a fluid-saturated porous layer confined vertically by adiabatic limits for the Darcy model is thoroughly analyzed. With consistent heat sources in both layers, this composite layer is subjected to three temperature profiles with Marangoni effects. The fluid-saturated porous region's lower boundary is a rigid surface, while the fluid region's upper boundary is a free surface. For the system of ordinary differential equations, the thermal surface-tension-driven (Marangoni) number, which also happens to be the Eigenvalue, is solved in closed form. The three different temperature profiles are investigated, the thermal surface-tension-driven (Marangoni) numbers are calculated analytically, and the effects of the heat source/sink are studied in terms of corrected internal Rayleigh numbers. Graphs are used to show how different parameters have an impact on the onset of triple-diffusive convection. The study's parameters have a greater influence on porous layer dominant composite layer systems than on fluid layer dominant composite layer systems. Finally, porous parameters and corrected internal Rayleigh numbers are stabilize the system, and solute1 Marangoni number and ratio of solute2 diffusivity to thermal diffusivity of fluid are destabilize the system.

Late order loss for difficulty handling (loading and unloading) activities left an alarm message to make traditional transportation handling for distribution e-commerce more accessible through mitigating it to semi-auto actions. This article discusses the idea of Vehicle Containers made up of Permutational Drawers, i.e., VCPD, that ensure ergonomic handling. The proposed Ergonomic Digital Twin (EDT) manages the VCPD by the Internet of things, i.e., IoT. The VCPD object has two dimensions: drawers' size and motion mechanism. These targets are implemented via establishing the digital twins' model, i.e., DT, for these drawers to test its qualifying for implementation, mainly if supported by IoT. There is still much confusion regarding the DT and how it will apply to the VCPD in medium-sized schemes for transportation enterprises. This work activates the IoT to bolster and simplify transportation activities through designing VCPD and control via a unified framework having several standard steps to reduce execution time, effort, and transportation costs.

The background of this study is relevant to parking facilities at shopping malls in the Kingdom of Saudi Arabia (KSA), where all parking services are mostly free, with very few exceptions. Demand on parking places at shopping malls and recreational areas in Saudi cities are generally very high. This is partly because most of the entertaining, shopping, and recreational areas are indoors and are typically located at shopping malls with huge parking provision. With the vast increase in car ownership and use in the country over the past few decades, a consequent increase in demand on roads and parking facilities has been observed, which has no doubt resulted in further congestion. This study aims to investigate the willingness to pay to save time searching for a parking place at shopping malls in Riyadh city in the KSA. The methodology includes interviewing shoppers in shopping mall car parks and asking about their search time for a parking space and their willingness to pay to save search time, as well as to report on their socio-economic characteristics including age, gender, employment, education, car ownership, and income. The outcome of this study shows that on average, shoppers spend about 9 min searching for a parking place for their shopping and recreational trips. The results also show that, on average, shoppers reported that they go shopping, eating out, etc., about three times per week, and the average willingness to pay to save time searching for parking space is about 10 Saudi Riyal (about 2.7 USD) per visit. The modelling results show that there is a higher willingness to pay from the middle income and car-ownership categories of the population than from the highest income and car ownership groups. This might reflect the fact that the middle-income groups are much more dependent on themselves to drive their cars and search for a parking space every time, while those of higher incomes could possibly rely on their private drivers most of the times to drive them and park their cars. This paper contributes to the literature by providing a first understanding on how demand for parking facilities is affected by various socio-economic factors and the willingness to pay to save search time at these parking locations. The implications of the outcome of this research will be of use for decision makers and city authorities in planning travel demand management policies and programs that aim at reducing demand on private cars and achieving sustainability.

The significance of thermal conductivity, convection, and heat transportation of hybrid nanofluids (HNFs) based on different nanoparticles has enhanced an integral part in numerous industrial and natural processes. In this article, a fractionalized Oldroyd-B HNF along with other significant effects, such as Newtonian heating, constant concentration, and the wall slip condition on temperature close to an infinitely vertical flat plate, is examined. Aluminum oxide (Al2O3) and ferro-ferric oxide (Fe3O4) are the supposed nanoparticles, and water (H2O) and sodium alginate (C6H9NaO7) serve as the base fluids. For generalized memory effects, an innovative fractional model is developed based on the recently proposed Atangana–Baleanu time-fractional (AB) derivative through generalized Fourier and Fick’s law. This Laplace transform technique is used to solve the fractional governing equations of dimensionless temperature, velocity, and concentration profiles. The physical effects of diverse flow parameters are discussed and exhibited graphically by Mathcad software. We have considered 0.15≤α≤0.85,2≤Pr⁡≤9,5≤Gr≤20,0.2≤ϕ1,ϕ2≤0.8,3.5≤Gm≤8, 0.1≤ Sc ≤0.8, and 0.3≤λ1,λ2≤1.7. Moreover, for validation of our present results, some limiting models, such as classical Maxwell and Newtonian fluid models, are recovered from the fractional Oldroyd-B fluid model. Furthermore, comparing the results between Oldroyd-B, Maxwell, and viscous fluid models for both classical and fractional cases, Stehfest and Tzou numerical methods are also employed to secure the validity of our solutions. Moreover, it is visualized that for a short time, temperature and momentum profiles are decayed for larger values of α, and this effect is reversed for a long time. Furthermore, the energy and velocity profiles are higher for water-based HNFs than those for the sodium alginate-based HNF.

The functional effects of medications, such as those that slow down and calm the body, have been investigated for the polarized diffusion coefficient based on the subsequent increase through magnetism. This study examines generalized Mittag–Lefer kernel-based fractional derivatives in MHD Brinkman-type fluids under bioconvection that contain hybrid titanium dioxide (TiO2) and silver (Ag) nanoparticles with water (H2O) and sodium alginate (NaC6H7O6) as the base fluids. Atangana–Baleanu (AB) and Caputo–Fabrizio (CF) fractional derivatives, which are two contemporary definitions of fractional-order derivatives with a memory effect, were used to explore the modified fractional model utilizing the Laplace transformation and certain numerical algorithms. The impacts of restrictions on various nanoparticles were investigated and graphically displayed. We observed that the volumetric fraction improvement controls the fluid velocity by slowing it down. The water-based hybrid nanofluid has a greater influence on the temperature and momentum fields than the sodium alginate-based hybrid nanofluid due to the physical characteristics of the explored nanoparticles and base fluids. Additionally, the memory effect causes a higher substantial value for the AB-fractional derivative of the velocity profile than the CF-fractional derivative.

The fluid flow through blunt bodies that are yawed and un-yawed frequently happens in many engineering applications. The practical significance of deep-water applications such as propagation control, splitting the boundary layer over submerged blocks, and preventing recirculation bubbles is explained by the fluid flow across a yawed cylinder. The current work examined the mixed convective flow and convective heat transfer by incorporating water-based graphene oxide nanofluid around a yawed cylinder with viscous dissipation and irregular heat source/sink. To investigate the heat diffusion across the system of buoyancy effects, the mathematical formulation of the problem was modeled in terms of coupled, nonlinear partial differential equations. The boundary value problem of the fourth-order (bvp4c) solver was operated to find the non-similarity solution. The outcomes indicated that the velocity in both directions enlarged owing to the higher impacts of yaw angle for the phenomenon of assisting flow but decreased for the instance of opposing flow, while the temperature of nanofluid increased because of heightened estimations of yaw angle for both assisting and opposing flows. In addition, with larger impacts of nanoparticle volume fraction, the shear stresses were enhanced by about 0.76% and 0.93% for the case of assisting flow, while for the case of opposing flow, they improved by almost 0.65% and 1.38%, respectively.

Recycling plastic waste (RPW) benefits the ecological footprint. Therefore, the authors test its mixing by magnetic hydrodynamic MHD nanofluid materials such as alumina in two sizes (βcore,βskin) prepared into a new device called the incubator installed in the desktop injection machine to enhance its solubility by taking advantage of the mixture’s heat via defining the oblique stagnation-point slip flow (OSPSF) of a nanofluid in two dimensions. The paper has been innovative in mathematically identifying the operating parameters’ values for the injection flow mechanism (IFM) via controlling in Riga magnetic field and piston orifice pressure using a meta-heuristic algorithm called WSA. The proposed (IFM) is used to experimentally enhance the mixture properties via parameters’ control to meet the output quality and predict the control equation for the Riga plate. IFM controls the amount of pushed nanoparticles in the mixture with a ratio of plastic to aluminum approximate by 96.1%: 3.9%. The defects were reduced by approximately 23.21%, with an increasing system performance of 70.98%.

The fractional model has been developed for the thermal flow of hybrid nanofluid due to the inclined surface. The thermal investigation of the hybrid nanomaterial is predicted by utilizing the molybdenum disulphide nanoparticles and graphene oxide nanomaterials. The flow computations for mixed convection flow of nanoparticles and base fluids are performed due to vertical oscillating plate. The simulations for the formulated model have been done ρ-Laplace transform technique for Caputo fractional simulations. Definitions of Mittage–Leffler function and ρ-Laplace transform are also presented for the governing model. The application of updated definitions of ρ-Laplace transform for the Caputo fractional model is quite interesting unlike traditional Laplace transforms. The comparative investigation for both types of nanoparticles is performed for heat and mass transfer rates. It is observed that the heat enhancement rate due to water-based nanoparticles is relatively impressive compared to the kerosene oil-based nanomaterials.

Enhanced heat transport in advanced nanofluids (ternary hybrid nanofluids) is one of the major demands of the time and is potentially contributing in food processing to maintain the temperature of building, cooling of electronic devices, paint industries and biomedical engineering. Therefore, an efficient heat transport model is developed in this study and innovative ternary mixture [(Al2O3-CuO-Ag)] along with feasible thermophysical attributes comprising the effects of ternary nanoparticles and similarity equations are exercised to obtain the desired sort of nanoliquid model. This model is related to vertically oriented cylinder with novel upgradation of permeability, upthrust forces and nonlinear solar thermal radiations. In the next stage, mathematical treatment of [(Al2O3-CuO-Ag)/H2O]thnf is done and successfully achieved the desired convergence and then organized the graphical results. The furnished results disclosed that tri-composites-based nanofluid has low velocity than hybrid and common nanofluids. Moreover, temperature in [(Al2O3-CuO-Ag)/H2O]thnf is dominant over both hybrid and mono nanofluids. The integrated effects of nonlinear thermal radiations are of much interest in the temperature enhancement and observed that Rd and [Formula: see text] are better for thermal improvement.

The hydrothermal characteristics of (Ag+TiO2+H2O) hybrid nanofluid three dimensional flow between two vertical plates, in which the right permeable plate stretches as well as rotates, are investigated by employing varying magnetic, heat and radiation fluxes. The motion is governed by coupled PDEs (nonlinear) obeying suitable boundary conditions. The PDEs coupled system is transformed to a coupled set of nonlinear ODEs employing appropriate similarity transformation relations. The resultant equations are numerically solved through the bv4c solver. The impact of the changing strength of associated parameters on the flow is investigated graphically and through tables. It has been found that the velocity gradient and velocity initially increase and then decrease with increasing Grashof number values in both the suction and injection cases. The enhancing magnetic field first augments and then lowers the velocity gradient in the presence of radiation source of maximum strength. The increasing strength of injection parameter drops the velocity. The temperature distribution in the fluid increases with the increasing Eckert number, radiation flux and heat strength and nanomaterial concentration, and depreciates with the enhancing injection parameter values and Prandtl number. The Cfx increases with a higher magnetic field magnitude and nanomaterial concentration, and declines with an increasing Grashof number. The results obtained are compared with the available literature in the form of tables.

The role of nanofluids in the development of many electronic devices at the industrial level is very significant. This investigation describes the thermal exploration for a bioconvective flow of Maxwell nanoparticles over stretching and revolving the cylinder placed in a porous medium. The fluid flow is in contact with chemically reactive activation energy. The swirling flow is induced by the stretching rotary cylinder. The magnetic effect of constant strength B0 is practiced to the flow system in combination with thermally radiative effects and a heat source/sink for controlling the thermal effects upon the flow system. The thermophoretic and Brownian motion characteristics, due to the nanofluid flow, are captured by implementing the Buongiorno model. The central focus of this study is to explore the thermal and mass transfer for the flow problem accompanied by motile microorganisms. The governing equations have been converted to the dimensionless form with similar variables, and the homotopy analysis method (HAM) has then been applied for solution. It has been concluded in this investigation that fluid flow decays for escalation in the Maxwell, porosity, and magnetic parameters, and Forchheimer and bioconvection Rayleigh numbers, while upsurges with the augmenting values of the Buoyancy factor. With the increasing values of the Brownian number, thermophoretic and radiation factors upsurge the thermal profiles and decline the concentration profiles. Moreover, the density of motile microorganisms declines with the expansion in the Peclet number. The range for η is taken from 0 to seven to get the convergence of the graph.

Scholars seek to recycle wasted energy to produce electricity by integrating thermoelectric generators (TEGs) with internal combustion engines (ICE), which rely on the electrical conductivity, β, of the thermal conductor strips. The TEG legs are alloyed from iron, aluminum and copper in a strip shape with specific characteristics that guarantee maximum thermo-electric transformation, which has fluctuated between a uniform, Gaussian, and exponential distribution according to the structure of the alloy. The ICE exhaust and intake gates were chosen as the TEG sides. The digital simulator twin model checks the integration efficiency through two sequential stages, beginning with recording the causes of thermal conductivity failure via filming and extracting their data by neural network procedures in the feed of the second stage, which reveal that the cracks are a major obstacle in reducing the TEG-generated power. Therefore, the interest of the second stage is predicting the cracks’ positions, Pi,j, and their intensity, QP, based on the ant colony algorithm which recruits imaging data (STTF-NN-ACO) to install the thermal conductors far away from the cracks’ positions. The proposed metaheuristic (STTF-NN-ACO) verification shows superiority in the prediction over [Mat-ACO] by 8.2% and boosts the TEGs’ efficiency by 32.21%. Moreover, increasing the total generated power by 12.15% and working hours of TEG by 20.39%, reflects reduced fuel consumption by up to 19.63%.

Given the importance and use of electrically conducted nanofluids, this work aims to examine an engine-oil-based nanofluid including various nanoparticles. In the current study, a fractional model for inspecting the thermal aspect of a Brinkman-type nanofluid, composed of (molybdenum disulfide (MOS2) and graphene oxide (GO) nanoparticles flows on an oscillating infinite inclined plate, which characterizes an asymmetrical fluid flow, heat, and mass transfer. Furthermore, the Newtonian heating effect, magnetic field, and slip boundary conditions were taken into account. The objectives for implementing the Prabhakar-like fractional model are justified because this fractional algorithm has contemporary definitions with no singularity restrictions. Furthermore, the guided fractional model was solved using the Laplace transform and several inverse methods. The obtained symmetrical solutions have been visually analyzed to investigate the physics of several relevant flow parameters on the governed equations. Some exceptional cases for the momentum field are compiled to see the physical analysis of the flowing fluid symmetry. The results show that the thermal enhancement can be progressively improved with the interaction of the molybdenum disulfide-engine oil-based nanofluid suspension, rather than with the graphene oxide mixed nanoparticle fluid. Furthermore, the temperature and momentum profiles enhance due to the factional parameters for molybdenum disulfide and the graphene oxide-engine oil-based nanofluid suspension. This study’s graphical and numerical comparison with the existing literature has shown a very close resemblance with the present work, which provides confidence that the unavailable results are accurate. The results show that an increase improved the heat transmission in the solid nanoparticle volume fractions. In addition, the increment in the mass and heat transfer was analyzed in the numerical evaluation, while the shear stress was enhanced with the enhancement in the Prabhakar fractional parameter α.

The intention of this study is to carry out a numerical investigation of time-dependent magneto-hydro-dynamics (MHD) Eyring–Powell liquid by taking a moving/static wedge with Darcy-Forchheimer relation. Thermal radiation was taken into account for upcoming solar radiation, and the idea of bioconvection is also considered for regulating the unsystematic exertion of floating nanoparticles. The novel idea of this work was to stabilized nanoparticles through the bioconvection phenomena. Brownian motion and thermophoresis effects are combined in the most current revision of the nanofluid model. Fluid viscosity and thermal conductivity that depend on temperature are predominant. The extremely nonlinear system of equations comprising partial differential equations (PDEs) with the boundary conditions are converted into ordinary differential equations (ODEs) through an appropriate suitable approach. The reformed equations are then operated numerically with the use of the well-known Lobatto IIIa formula. The variations of different variables on velocity, concentration, temperature and motile microorganism graphs are discussed as well as force friction, the Nusselt, Sherwood, and the motile density organism numbers. It is observed that Forchheimer number Fr decline the velocity field in the case of static and moving wedge. Furthermore, the motile density profiles are deprecated by higher values of the bio convective Lewis number and Peclet number. Current results have been related to the literature indicated aforementioned and are found to be great achievement.

Curved veins and arteries make up the human cardiovascular system, and the peristalsis process underlies the blood flowing in these ducts. The blood flow in the presence of hybrid nanoparticles through a tapered complex wavy curved channel is numerically investigated. The behavior of the blood is characterized by the Casson fluid model while the physical properties of iron (Fe3O4) and copper (Cu) are used in the analysis. The fundamental laws of mass, momentum and energy give rise the system of nonlinear coupled partial differential equations which are normalized using the variables, and the resulting set of governing relations are simplified in view of a smaller Reynolds model approach. The numerical simulations are performed using the computational software Mathematica’s built-in ND scheme. It is noted that the velocity of the blood is abated by the nanoparticles’ concentration and assisted in the non-uniform channel core. Furthermore, the nanoparticles’ volume fraction and the dimensionless curvature of the channel reduce the temperature profile.

The thermal enhancement of industrial and engineering processes with interaction of nanofluids is exclusively important and presents applications in extrusion systems, heat transfer devices, electronic chips, chemical reactions, nuclear processes, etc. Owing to such motivated significance of nanofluids, the aim of this investigation is to present the heat and mass transfer phenomenon in the Couple stress nanofluid flow containing the microorganism due to oscillatory stretched surface. Additionally, the Darcy–Forchheimer applications, nonuniform heat source and nonlinear thermal radiation effects are considered. The modification in the concentration equation is done by activation energy. The independent variables in the defined flow system are decreased via suitable variables. The computation is simulated using the homotopy analysis method. It is noticed that the magnitude of velocity periodically decreases for larger values of suction parameter and inertia coefficient. The presence of an external heat source parameter enhanced the temperature profile. Moreover, the increment in the suction parameter improves the heat and mass transfer rate.

Curved veins and arteries make up the human cardiovascular system, and the peristalsis process underlies the blood flowing in these ducts. The blood flow in the presence of hybrid nanoparticles through a tapered complex wavy curved channel is numerically investigated. The behavior of the blood is characterized by the Casson fluid model while the physical properties of iron (Fe

In this paper, the 3D Darcy–Forchheimer flow model (TDDF-FM) is discussed by utilizing the artificial intelligence-based backpropagated neural networks with the algorithm of Levenberg–Marquardt (BNN-ALM) along with the convective conditions. The effects of Brownian diffusion and thermophoresis are also examined. The governing partial differential equations are transformed into a system of ODEs. Lobatto IIIA method is used to interpret the reference dataset of BNN-ALM for different scenarios of TDDF-FM by variation of porosity parameter, Forchheimer parameter, ratio parameter, Prandtl number, Biot number, Brownian motion parameter, Schmidt number, strength parameter of homogeneous reaction and thermophoresis parameter. The solutions are computed for the designed TDDF-FM by testing, training and validation processes of BNN-ALM. The performance analysis of the designed BNN-ALM is validated by histogram analysis, regression studies and the results of mean square error (MSE). Graphs are presented for temperature profile, concentration profile and concentration rate profile. The increasing values of porosity parameter, Forchheimer parameter and Biot number enhance the temperature distribution, whereas the temperature profile shows a decreasing behavior with the increase in Prandtl number and ratio parameter. The concentration profile increases with the increase in porosity parameter, Forchheimer parameter and thermophoresis parameter and it decreases with the increasing behavior of Brownian motion parameter, ratio parameter and Schmidt number. The concentration rate profile decreases with the increase in porosity parameter, Forchheimer parameter and strength parameter of homogeneous reaction and it increases with the ratio parameter. The best performance values for different cases of scenarios are 1.42E−08, 1.70E−08, 1.78E−08, 1.61E−08, 2.43E−08, 1.05E−08, 1.30E−08, 1.59E−08 and 2.31E−08, attained at 215, 186, 178, 99, 125, 213, 187, 190 and 191 epochs. The values for the Gradient factor are 9.93E−08, 9.86E−08, 9.99E−08, 2.97E−07, 1.23E−07, 9.94E−08, 9.94E−08, 9.87E−08 and 9.94E−08, where the value of regression is [Formula: see text] for the training, testing and validation data.

The existence of man is dependent on nature, and this existence can be disturbed by either man-made devastations or by natural disasters. As a universal phenomenon in nature, symmetry has attracted the attention of scholars. The study of symmetry provides insights into physics, chemistry, biology, and mathematics. One of the most important characteristics in the expressive assessment and development of computational design techniques is symmetry. Yet, mathematical models are an important method of studying real-world systems. The symmetry reflected by such a mathematical model reveals the inherent symmetry of real-world systems. This study focuses on the contagious model of pine wilt disease and symmetry, employing the q-HATM (q-Homotopy Analysis Transform Method) to the leading fractional operator Atangana–Baleanu (AB) to arrive at better understanding. The outgrowths are exhibited in the forms of figures and tables. Finally, the paper helps to analyze the practical theory, assisting the prediction of its manner that corresponds to the guidelines when contemplating the replica.

The depletion of natural resources and greenhouse gas emissions related to the manufacture and use of ordinary Portland cement (OPC) pose serious concerns to the environment and human life. The present research focuses on using alternative binders to replace OPC. Geopolymer might be the best option because it requires waste materials enriched in aluminosilicate for its production. The research on geopolymer concrete (GPC) is growing rapidly. However, substantial effort and expenses are required to cast specimens, cures, and tests. Applying novel techniques for the said purpose is the key requirement for rapid and cost-effective research. In this research, supervised machine learning (SML) techniques, including two individual (decision tree (DT) and gene expression programming (GEP)) and two ensembled (bagging regressor (BR) and random forest (RF)) algorithms were employed to estimate the compressive strength (CS) of GPC. The validity and comparison of all the models were made using the coefficient of determination (R2), k-fold, and statistical assessments. It was noticed that the ensembled SML techniques performed better than the individual SML techniques in forecasting the CS of GPC. However, individual SML model results were also in the reasonable range. The R2 value for BR, RF, GEP, and DT models was 0.96, 0.95, 0.93, and 0.88, respectively. The models’ lower error values such as mean absolute error (MAE) and root mean square errors (RMSE) also verified the higher precision of ensemble SML methods. The RF (MAE = 2.585 MPa, RMSE = 3.702 MPa) and BR (MAE = 2.044 MPa, RMSE = 3.180) results are better than the DT (MAE = 4.136 MPa, RMSE = 6.256 MPa) and GEP (MAE = 3.102 MPa, RMSE = 4.049 MPa). The application of SML techniques will benefit the construction sector with fast and cost-effective methods for estimating the properties of materials.

The physiological systems and biological applications that have arisen during the past 15 years depend heavily on the microscale and nanoscale fluxes. Microchannels have been utilized to develop new diagnostic assays, examine cell adhesion and molecular transport, and replicate the fluid flow microenvironment of the circulatory system. The various uses of MHD boundary flow in engineering and technology are extensive, ranging from MHD power generators and the polymer industry to MHD flow meters and pumps and the spinning of filaments. In this investigation, the (Magnetohydrodynamic) MHD flow of Prandtl nanofluid is investigated along with mixed convection, energy activation, microorganism, and chemical reaction. The flow model is considered through partial differential equations in dimensionless form which is then integrated numerically via considering the Bvp4c technique. The outcome is numerous emerging physical parameters over velocity profile, temperature, mass concentration, and microorganism with the separate pertinent quantities such as the Prandtl fluid parameter, elastic fluid parameter, magnetic field, mixed convection parameter, activation energy, chemical reaction, Brownian motion, thermophoretic force, Prandtl number, and Schmidt number. The friction factor, rate of heat transfer and Sherwood number, and density of microbes are revealed numerically and graphically. The outcomes indicate that the Prandtl fluid parameter and elastic fluid parameter tend to enhance the velocity profile. It is also noted that the Prandtl fluid parameter depreciates the thermal rate with the addition of the concentration profile while the opposite trend is recorded for activation energy. Obtained numerical outcomes are correspondingly compared with the current statistics in limiting cases and a close match is obtained.

Water has attracted plenty of attention as a lubricant for manufacturing due to the fact that it is inexpensive, environmentally friendly, and efficient. Because of their outstanding mechanical capabilities, water dispensability, and range of real applications, graphene oxide (GO) materials have the potential to augment the effectiveness of water lubrication. With this encouragement, we inspect the impact of induced magnetism on the fluid flow near a stagnation point dispended with water-based GO nanoparticles caused by a movable surface with a homogeneous–heterogeneous chemical reaction. The leading equations and their related boundary constraints are first transformed into a non-dimensional form through the utilization of the similarity technique. The consequent equations are then numerically solved by employing the bvp4c scheme. Those figures are used to exemplify the stimulation of the relevant constraints on the fluid flow, induced magnetic profiles, temperature profiles, concentration profiles, heat transfer, and friction factor. It is observed that the nanoparticle’s volume fraction enhances the heat transfer rate, as well as the friction factor. The heat transfer and friction factor escalate by almost 11.71% and 0.96% for the respective upper-branch solutions due to the larger impacts of nanoparticles’ volume fractions, while for the lower-branch solutions, they are augmented at about 21.8% and 0.66%, respectively. In addition, double solutions can be found in the limited values of a movable parameter.

In many industries, extremely high-performance cooling is a crucial requirement. However, the fundamental challenge to developing energy-efficient heat transfer fluids required for cooling is insufficient thermal conductivity. In this case, the utilization of nanofluid is effective to overcome these challenges. The current study aims to examine the two-dimensional (2D) stretching wall jet heat transfer fluid flow induced by a water-based alumina nanofluid embedded in a porous medium with buoyancy force. In addition, irregular heat sink/source and slip effects are assessed. The leading partial differential equations are changed into ordinary differential equations by incorporating similarity variables, then these equations are computationally or numerically worked out via the boundary-value problem of fourth-order (bvp4c) technique. The pertinent factors influencing the symmetry of the hydrothermal performance including friction factor, velocity, and temperature profiles, are illustrated using tables and graphs. The symmetrical outcomes reveal that the velocity declines in the presence of nanoparticles, whereas the temperature uplifts both assisting and opposing flows. Moreover, the friction factor augments due to porosity while the heat transfer rate declines.

The current exploration aims to inspect the features of thermal radiation on the buoyancy or mixed convective fluid flow induced by nanofluid through a stretching permeable bended sheet. The impact of activation energy and binary reaction along with slip migration is taken into account to discuss the fine points of water-based alumina nanoparticle flow. The structure of the curved sheet is assumed to be stretchable and the bended texture is coiled within a circular section with radius Rb. The similarity technique is utilized to reduce the leading partial differential equations into ordinary differential equations. These reduced equations are then deciphered numerically by employing the bvp4c method. The outcomes of the model were constructed in the form of several figures and bar graphs for the case of opposing and assisting flows with varying distinct embedded control parameters. The results display that the velocity field curves escalate with a higher radius of curvature parameter while temperature and concentration profiles shrink. More precisely, the outcomes show that the temperature distribution profile increases with the increase in nanoparticle’s volume fraction as well as thermal radiation parameter. Meanwhile, the concentration and velocity fields are decelerated with higher impacts of nanoparticle volume fraction. In addition, the heat and mass transfer rates were significantly improved for the higher value of the radiation and Schmidt number. On the other hand, the growing values of the velocity slip factor decrease the shear stress. Furthermore, the results are compared with the previous results in the limiting cases and observed a tremendous harmony.

This paper aims to optimize the losses of the current manufacturing systems to perform the Just in Time (JIT) system and minimize the time, labor, and material in the manufacturing process. Pull systems, which have a famous name of the Smart Kanban system, are one of the methodologies to implement the JIT system. The setting of manufacturing system frameworks offers intriguing capabilities to improve the performance of pull-controlled creation frameworks. Smart Kanban can be utilized, rather than actual cards, and the data conversion about the manufacturing settings, is accessible through sensors. Since a Just-in-Time system does not include a buffer, any interruption to the system can cause the process to stop quite quickly, so security is necessary for the JIT improvement. However, those systems have recently been unguarded to security threats as they introduce general-purpose technologies. From the viewpoint of the system, a security measure is implemented for pull system methods to check for potential threats and analyze vulnerabilities of the pull system. The Flower Pollination Algorithm (FPA) is used as a novel multiobjective technique to optimize different types of cost and time. The experimental results show that the proposed algorithm has robust security efficiency, as well as reduces cost and time consumption.