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Recently a considerable amount of attention has been directed towards the technological advancements in the study of arterial stenosis. The deposition of adipose tissues and saturated fatty acids and the abnormal growth of flesh, narrows the arteries, leading to restricted blood flow. This causes cardiovascular diseases like atherosclerosis, atherogenesis, atheroma, etc. Considering this the present research paper develops a Casson fluid model to investigate magnetohydrodynamic peristaltic transport of the passage of blood through slightly stenosed arteries due to the influence of copper (Cu) and alumina (Al2O3) nanoparticles. The problem is formulated using appropriate mathematical models employing non-dimensional parameters and stenosis approximations. The study has its applications in the field of medicine. The outcome of this work is that it helps to handle many heart conditions. The findings of this investigation may have benefits in various academic fields, including pharmaceuticals and other industries. In addition, they are remarkably beneficial in the treatment of numerous cardiovascular diseases.

The significant increase in thermal efficiency and the rate of energy exchange used in fuel dynamics and automobile coolants are leading to a better understanding of nanofluids. This computational analysis explores the thermal conductivity performance for radiative cross-flow of a nanofluid across an expanding/constricting sheet with a suction effect as a result of its application. To compute or calculate the magnificent point of nanofluid flow, the entropy, and asymmetrical heat source/sink effects are also elicited. The boundary layers traverse a stream-wise procedure for expanding and contracting sheets. Additionally, the study examines the features of heat transfer and cross-flow of nanofluids using numerical simulations. By employing similarity variables, the basic PDE equations of the current model are transformed into ODEs, and they are subsequently evaluated using the bvp4c method. Therefore, the effects of embedded flow variables on drag force, heat transfer rate, and entropy generation profiles have been framed using parametric research. Multiple solutions are offered for a specific range of the contracting parameter as well as the mass suction parameter. In addition, the heat transfer rate accelerates due to the heat source and decelerates due to the heat sink. The literature that is already published has been compared favorably, and it reveals many commonalities.

Universities and colleges play a pivotal role in the pursuit of a future that is sustainable through their pedagogical efforts and the execution of state-of-the-art research endeavors aimed at mitigating the effects of climate change. Higher Education Institutions (HEIs) serve as crucial catalysts in advancing sustainable development. HEIs are increasingly embracing precise measures to reduce their carbon footprint (CF) while also educating students on global sustainability. These nano-methods provide a quantitative framework for assessing a campus's sustainability efforts in line with Green Campus (GC) initiatives to lower carbon emissions align with GC goals. This study employs K-means clustering to analyze the integration of green and low-carbon principles in higher education political and ideological studies. Its goal is to identify patterns, assess teaching effectiveness, and improve sustainability education, aligning with Green Campus initiatives to enhance institutional contributions to sustainable growth through informed pedagogical strategies. Input data includes curriculum content, teaching methods, student engagement, and institutional goals related to sustainability. Seeking to improve sustainability education align with Green Campus initiatives, higher education can strategically enhance their contributions to long-term sustainability and growth through effective pedagogical approaches. Cluster 3 has the lowest WCSS value of 1200, indicating tighter cohesion and less variability within this cluster compared to Cluster 1 (1500) and Cluster 2 (1800). Cluster 3 stands out with the highest silhouette score of 0.7, suggesting well-defined and distinct clusters, while Cluster 2 has the lowest score of 0.4, indicating some overlap or ambiguity in data points. Cluster 1 has the lowest Davies-Bouldin Index of 0.4, implying better separation between clusters compared to Cluster 2 (0.6) and Cluster 3 (0.5). Cluster 3 is well-defined and cohesive, showing strong integration of green practices. Cluster 1 displays good separation and cohesion, while Cluster 2 requires refinement due to potential overlap in sustainability integration.

Abstract Access to dependable and environmentally friendly energy sources is critical to a country's economic growth and long-term development. As countries seek greener energy alternatives, the interaction of environmental elements, temperature, and sunlight becomes more critical in utilizing renewable energy sources such as wind and bioenergy. Solar power has received much attention due to extraordinary efficiency advances. under this context, the present work focus on solar radiation and chemical processes in the presence of modified ternary hybrid nanofluids (THNFs) circulating over an exponentially stretched surface in both aiding flow (A-F) and opposing flow (O-F) circumstances. The primary objective of this investigation is to dive into the complicated dynamics of these structures, which are distinguished by complex interactions involving radiation, chemical reactions, and the movement of fluids. We construct reduced ordinary differential equations from the governing equations using suitable similarity transformations, which allows for a more in-depth examination of the liquid's behavior. Numerical simulations using the Runge–Kutta Fehlberg (RKF) approach and shooting techniques are used to understand the underlying difficulties of these reduced equations. The results show that thermal radiation improves heat transmission substantially under O-F circumstances in contrast to A-F conditions. Furthermore, the reaction rate parameter has an exciting connection with concentration levels, with greater rates corresponding to lower concentrations. Furthermore, compared to the O-F scenario, the A-F scenario promotes higher heat transfer in the context of a modified nanofluid. Rising reaction rate and solid fraction volume enhanced mass transfer rate. The rate of thermal distribution in THNFs improves from 0.13 to 20.4% in A-F and 0.16 to 15.06% in O-F case when compared to HNFs. This study has real-world implications in several fields, including developing more efficient solar water heaters, solar thermal generating plants, and energy-saving air conditioners.

Online supply chain management (OSCM) is the smart way to deal with the vast amounts of data that come in from customers in a disorganized system to meet the quantities, volumes, and types of customer packages during both delivery and pick-up phases using a new design of vehicle boxes managed by IoT and to track their requests based on scheduling requests and sorting them to make a Hamiltonian route that guarantees the shortest travel distance. The OSCM framework consists of two sequential phases. 1st phase has four recruitment stages. The 1st stage discusses exploration resources (the relationship between the client and the vehicle) using IoT to receive customers' requests (Heijunka growth radius), then moves to exploration maturity to build a one-way Hamiltonian growth route direction. The 1st stage is based on tackling a Heijunka matrix fed through deep learning to classify the matrix into many conditional clusters according to customers' request forecasting and make the prediction value, which is the stop condition of cluster radius through next three stages. This study finds that XGboost outperforms Ada-boost by 14.352 % in the prediction stage. A heuristic rule based on NWBS enhances the FP-Growth algorithm over ECLAT by 7.648 % in the classification stage. Phase II is interested in reducing load and unloading activity time. This problem describes needing more than a different service at the same point (i.e., chaotic and unstable interaction leads to unstable delivery). Therefore, the online scheduling and tracking of the logistic routing using the IoT that Smart Lean Heijunka supports will enhance the SCM, increasing the visited points by 31.2 % and improving the profit by 41 %.

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.

The current study addresses the flow of steady electrically conducting hybrid nanofluid (HNF) across an impermeable slender stretchable sheet. The flow distribution takes into consideration the effects of variable magnetic fields, heat production, Hall current and chemical reactions. A computational model is established for the purpose to amplify the energy communication rate and enhance the productivity and performance of thermal energy propagation for several industrial and biological purposes. The hybrid nanofluid is comprised of silver and magnesium oxide nanomaterials in the working fluid water. Among transition metals and alloys, magnesium oxide and silver nanoparticles (NPs) have been extensively documented to have broad-spectrum antibacterial properties. Silver NPs are the most extensively employed inorganic NP, having several applications in biomaterial detection and antibacterial actions. The scenario has been expressed as a system of PDEs. Which are simplified to the system of ODEs through similarity replacements. The computing approach PCM is used to subsequently evaluate the acquired 1st order differential equations. The outcomes are checked with the bvp4c package and existing literature for consistency and validity. It has been noticed that the axial velocity profile enhances with the effect of Hall current m and velocity power index constraint n, while reducing with the variation of nanoparticles volume friction ϕ1,ϕ2 and slender sheet wall thickness parameter δ.

The properties of nanoparticles in the working fluid are affected by many external factors and it further influences the effective properties of the resulting nanofluid. To study the heat transference mechanism in nanofluids, the inclusion of such factors is quite important as it provides the exact illustration of the mechanism. One such factor is the nanoparticle aggregation effect. Authors have studied the titania–ethylene glycol nanofluid (TiO2/EG NF) flow over a wedge with nanoparticle aggregation effect. Through this communication, authors have attempted to make a development on the Falkner-Skan problem. The flow is developed in the presence of the suction/injection effects, mixed convection, thermal radiation, porous medium, and non-uniform heat source/sink. To account for the influence of nanoparticle aggregation, revised forms of the Maxwell and Bruggeman models and the Krieger-Dougherty model are employed to estimate the effective thermal conductivity and viscosity of TiO2/EG NF, respectively. The aforementioned modified models developed for TiO2/EG NF gave a soundly close agreement with the experimental data. The governing equations are numerically solved employing the “bvp4c function in MATLAB”. The effect of the primary relevant parameters on the velocity, temperature, and heat transmission rate is depicted graphically. The heat transmission rate at the surface is higher with aggregated nanoparticles in comparison to its absence. The higher NPs volume fraction and the aggregation effect enhance the effective viscosity, the fluid becomes denser, and as a result, the velocity decreases. The outcomes of this study will be useful in many fields that utilize applications of flow over wedge such as in raw oil extraction, storage of nuclear waste, insulating heat exchangers, etc.

The effect of heat and mass transfer on mixed convection flow field with porous matrix in a vertical channel has investigated analytically. The analytical solutions of the coupled nonlinear differential equations are obtained for velocity, temperatures and concentrations are showed graphically. The results obtained analytically by using regular perturbation method are considered to be favorable as no such investigations are performed previously. The governing equations have been made smaller than Non-linear ordinary differential equations by means of flow parameters. Investigations are carried out on the flow characteristics for different values of Grashof number, Reynolds number, Brinkman number, heat generation/absorption parameter and porous parameter. It is found that an increases in the Grashof number cause the buoyancy to increase, which in turn causes the fluid flow for heat generation and absorption to increase.

Energy is essential for a nation's economic growth. Energy is recognized in contemporary society as being crucial to the development of quality of life and sustainability. The environment transforms/absorbs heat and sunlight in a variety of ways. Some of these transitions lead to the flow of renewable energy sources like wind and biomass. Solar energy has become one of the promising alternative energy sources in the future because to the improvements made to enhance its performance. In this context, the impact of solar radiation on modified nanofluid flow over an exponential stretching sheet is examined. Using the proper similarity transformations, the governing equations for the flow assumptions are reduced to ordinary differential equations. The numerical simulation of these simplified equations is then performed using the Runge-Kutta Fehlberg method and the shooting methodology. With the aid of graphs and tables, the effects of numerous parameters on the involved fields are described. Results reveal that the modified nano liquid shows increased heat transport for opposing flow situation than the assisting flow situation for incremented values of porosity parameter and volume fraction. The modified nanoliquid shows increased heat transport for opposing flow situation with respect to augmented values of radiation parameter.

In this study, the triple diffusive Marangoni convection (TDMC) problem when a steady heat source is present in both layers and a vertical uniform magnetic field in a fluid-porous structure is investigated in closed form. The horizontally infinite fluid-porous structure, which is horizontally surrounded by adiabatic boundaries and subjected to basic uniform and non-uniform temperature profiles. For all three temperature profiles (TP), linear, parabolic and inverted parabolic, the eigenvalues, the thermal Marangoni numbers (TMNs) are determined in closed form for lower rigid and upper free boundaries with surface tension, depending on both temperature and concentrations. The effects of relevant parameters on the eigenvalues, hence on TDMC, against depth ratio are attempted for all TPs. It is noticed that, the inverted parabolic TP on TDMC in a composite layer is the most stable of all the three TPs, the linear TP is the most unstable one and the parabolic TP is the moderate one. The relevant physical parameters considered in the study are effective for porous layer dominant fluid-porous structures.

A number of scientists have indicated interest in the promising area of research that involves improving heat transmission by utilizing nanoparticles. The dynamic properties of nanofluids reflect several applications in the cooling process, thermal engineering, heat exchangers, magnetic cell separation, energy production, hyperthermia, etc. In light of the appealing implications of nanofluids, the current research aims to explore the melting process of MHD hybrid AA7072 and AA7075 alloy nanoparticles from a movable cylinder. It also incorporates the irregular Thompson and Troian slip effect to simulate the intricate features of the nanofluid flow. The primary nonlinear partial differential equations (NPDEs) are converted into nonlinear ordinary differential equations (NODEs) with the use of the similarity technique. These converted equations are unraveled numerically via applying the built-in program bvp4c in MATLAB. It is visually examined that physical parameters affect the temperature and skin friction. The outcomes suggest that double solutions are found in a certain range of movable cylinder parameter. In addition, the skin friction is decelerated due to the critical shear rate and velocity slip factors while it is enhanced with the influence of suction and nanoparticles volume fraction. Moreover, the temperature is uplifted due to nanoparticles volume fraction and is declined due to Stefan number. In case of quanitative descriptions, the skin friction boosted up by almost 3.64% and 1.18% for the particular upper and lower branch outcomes due to the superior influences of nanoparticle volume fraction. Also, the skin friction decelerated for the branch of upper and lower solutions at about 5.26% and 22.55%, respectively, due to the larger velocity slip parameter.

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 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 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.

The paper investigates the blood flow analysis through a non-uniform inclined channel by treating blood as a non-Newtonian Phan-Thien-Tanner (PTT) liquid. The impact of the chemical reaction and convective boundary conditions are studied in the current formulation. The interaction referring to such constraints report supporting behavior to simulates the particles motion in surgical systems. The fluid movement is regulated through complictatd systems for which solution is enables via perturbation procedure. The influences of diverse emerging parameters over several physiological quantities are scrutinized explicitly. It is also detected that geometric parameters like amplitudes, non-uniform parameters, and inclination angles play a vital role in operating liquid transport phenomena. The obtained results reveal that controlling of velocity due to magnetic constants is observed while thermal determination of particles showing an enhancing trend. Hence magnetic field is used in blood flow analysis such as a catheter, drug delivery, etc. The objective of applicable pertialtic model provdes assistant in hemodialysis.

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.

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.

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.

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.

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.

This study examines a viscous, incompressible, free-convective Casson fluid flow over an inclined plate, which characterizes an asymmetrical nanofluid flow and heat transfer behavior. Here, the two different nanofluids are basically made of molybdenum disulfide (MoS2) with CMC-based fluid and graphene oxide (GO) nanoparticles with CMC-based fluid to form a particular (CMC/MoS2) nanofluid and (CMC/GO) nanofluid. The Newtonian heating effect, slip boundary, porosity, and inclined magnetic effects are also considered. When memory effects are present, conventional PDEs are unable to investigate and evaluate the physical behavior of various flow parameters. We employed the Prabhakar fractional derivative, the best and most current fractional mathematical operator, to tackle the considered nanofluid problem. Using the integral transform approach, Laplace transforms, the non-dimensional governed model is converted into a fractional model and solved. The graphical analysis examines the influence and symmetrical behavior of significant physical and fractional parameters. The numerical effects of the Nusselt number, Sherwood number, and skin friction are also looked at, at various sundry values of the time. As a result, we conclude that increasing Prabhakar fractional constraints causes the thermal and momentum profiles to decelerate down. In addition, for two distinct values of time, 0.8 and 1.8, improvements of 3.823% and 5.042%, respectively, are observed in the mass transfer rate for the higher impacts of the Prabhakar fractional parameter, α, while the heat transfer rate declines by 10.065% and 15.908%, respectively. Also, the shear stress upsurges by 0.881% and 2.482%, respectively, for the change values of time 0.8 and 1.8 with higher values of Prabhakar fractional parameter α. Furthermore, with varying time, the accompanying criteria are satisfied, and the velocity and temperature fields both expand asymptotically in the y-direction and decline away from the plate. When comparing the two nanofluids, the (CMC/MoS2) nanofluid has a somewhat higher thermal and flow rate than the (CMC/GO) nanofluid. The studies indicated that increasing the volume percentage of nanoparticles causes heat transmission to be enriched.

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.

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.

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 radiated flow of magnetized viscous fluid subject to the viscous dissipation phenomenon is numerically studied. The radiative phenomenon is addressed with nonlinear relations. Further, analysis is performed by using the slip effects and convective thermal flow constraints. The transformed problem is numerically evaluated using the Keller Box method. The physical parameter effects, such as the magnetic parameter for the velocity profile, Prandtl number, Brownian motion parameter and Biot number for the energy profile and Lewis number, and the thermophoresis parameter for the concentration profile are discussed. The obtained results suggest applications in enhancing the heat transfer phenomenon, thermal system, energy generation, heat transmission devices, power generation, chemical reactions, etc.

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.

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.

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 thermal energy transfer characteristics during hybrid nanofluid migration are studied in the presence of a variable magnetic field, heat source, and radiation. The flow is governed by the conservation laws of mass, momentum, and energy, whereas it is modeled by the coupled set of nonlinear partial differential equations (PDEs). Suitable similarity transformations are employed to convert the developed set of PDEs to a nonlinear system of coupled ordinary differential equations (ODEs). The simplified system of ODEs is solved by using the well-established analytical procedure of homotopy analysis method (HAM). The effects of varying the strength of the physical parameters on the thermal energy transfer during hybrid nanofluid motion between two plates in which one of the plate is porous, rotating, as well as stretching are investigated through tables and two-dimensional graphs. The porosity is modeled through the Koo–Kleinstreuer model (KKL) correlation. The analysis reveals that the skin friction and Nusselt number augment with the increasing strength of the magnetic field and nanomaterials’ concentrations. The gradient in the fluid velocity has a dual dependence on the strength of the applied magnetic field and Grashof number and drops with the higher values of the unsteadiness parameter. The fluid velocity constricts with the enhancing magnetic field due to higher Lorentz forces, and it also drops with the increasing rotation rate. The enhancing buoyancy associated with higher Grashof number values augments the fluid velocity. The fluid’s temperature rises with the augmenting nanomaterial concentrations, Eckert number, nonsteadiness, heat source strength, and radiation parameter, while it drops with the higher Grashof number and Prandtl number. The applied technique of the HAM shows good convergence over a wide range of the convergent parameter. This work has potential applications in the development of efficient thermal energy transfer systems.

Almost every industrial and service enterprise adopts some form of Environmental Health and Safety (HSE) practices. However, there is no unified measurement implementation framework to resist losses exacerbated due to the “lack of safety precautions”, which must be considered one of the most dangerous Lean wastes because it jeopardizes the investment in the Hex-Bottom-Line (HBLs). Despite the widespread nature of the Lean approach, there no unified and collected framework to track and measure the effectiveness of the safety measures’ progress. Therefore, the enterprises resort to establishing their own tailored safety framework that maintains their competitiveness and sustainability. The enterprises must provide insight into safety deficiencies (i.e., faults and losses suffered) that have been measured via downtime spans and costs (Lean waste), reflecting the poor Lean Safety Performance Level (LSPL). This paper aims to shed light on two issues: (1) the adverse impact of the “lack of safety precautions” on LSPL caused by the absence of (2) a Lean Safety framework included in the Measurement and Analysis phases of Define Measure Analyze Identify Control (DMAIC). This framework is based on forecasting losses and faults according to their consumption time. The proposed framework appreciates the losses’ severity (time consumption and costs) via Fault Mode and Effect Forecasting (FMEF) aided by Artificial Neural Networks through sequential steps known as Safety Function Deployment (SFD).