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Abstract This study presents a sophisticated numerical simulation model for a forced circulation solar water heating system (FC-SWHs), specifically designed for the unique climatic conditions of Algeria. The model aims to cater to the hot water needs of single-family houses, with a daily consumption of 246 L. Utilizing a dynamic approach based on TRNSYS modeling, the system’s performance in Ain Temouchent’s climate was scrutinized. The model’s validation was conducted against literature results for the collector outlet temperature. Key findings include a maximum monthly average outlet temperature of 38 °C in September and a peak cumulative useful energy gain of 250 W in August. The auxiliary heating system displayed seasonal energy consumption variations, with the highest rate of 500 kJ/hr in May to maintain the water temperature at 60 °C. The energy input at the storage tank’s inlet and the consistent high-level energy output at the hot water outlet were analyzed, with the former peaking at 500 W in May. The system ensured an average water tank temperature (hot, middle and bottom) and water temperature after the mixer, suitable for consumption, ranging between 55 °C and 57 °C. For applications requiring cooler water, the mixer’s exit temperature was maintained at 47 °C. The study’s key findings reveal that the TRNSYS model predicts equal inlet and outlet flow rates for the tank, a condition that is particularly significant when the system operates with high-temperature water, starting at 55 °C. The flow rate at this temperature is lower, at 7 kg/hr, while the water mass flow rate exiting the mixer is higher, at 10.5 kg/hr. In terms of thermal performance, the system’s solar fraction (SF) and thermal efficiency were evaluated. The results indicate that the lowest average SF of 54% occurs in July, while the highest average SF of over 84% is observed in September. Throughout the other months, the SF consistently stays above 60%. The thermal efficiency of the system varies, ranging from 49 to 73% in January, 43–62% in April, 48–66% in July, and 53–69% in October. The novelty of this research lies in its climate-specific design, which addresses Algeria’s solar heating needs and challenges. Major contributions include a thorough analysis of energy efficiency metrics, seasonal auxiliary heating demands, and optimal system operation for residential applications, supporting Algeria’s goal of sustainable energy independence.

The present work examines that how the fins attached to the inner surface of a vertically oriented pipe affect the flow as well as thermal characteristic of the nanofluid flow when exposed to sunlight-induced heating. A definite thermal boundary condition together with fully established hydrodynamics and thermal conditions is applied that confirms uniform temperature along the sun-exposed pipe walls. Finite volume method, with computational efficiency and solution accuracy, is incorporated. A magnetic damping produces significant changes in the flow patterns within the pipe. A reduction in the velocity distribution is also caused by this damping force. The intensified applied magnetic field impact also changes the velocity distribution. It leads to a flattening of the velocity surface, indicating a decrease in velocity gradient within the flow field. The larger fins work as significant obstacles by altering flow direction and increasing velocity gradients near the solid surface. However, the higher Rayleigh numbers qualitatively change the thermal characteristics within the pipe. Finally, an artificial intelligence-based analysis is presented that correlates our research methodology with a Neural Fitting app. This neural network app is leveraged to enrich the accuracy of the present numerical technique and ensures a robust evaluation of the thermal signature of nanofluid flow within the pipe exposed to sunlight-induced heating.

The flow of fluids through porous media is commonly described using the Darcy model, therefore investigating hybrid nanofluids in this setting is rather new. The present work offers insightful information on how the hybrid nanofluids behave and function in porous medium. The study's conclusions may have an impact on a lot of different engineering applications like filtration systems, chemical reactors, and environmental engineering. The study concentrates on a hybrid nanofluid which consists of Cu and Al₂O₃ nanoparticles. The metallic nanoparticles such as copper have high thermal conductivity and non-metallic nanoparticles such as aluminum oxide are chemically stable and has high thermal resistance. This is the reason that the combination Cu-Al₂O₃ is believed to give better heat transfer composite than using individual nanofluids. By employing proper similarity transformation, the governing PDEs are turned into ODEs. To discretize these ODEs, the central finite difference method is used first. Then the successive over relaxation technique is utilized to numerically solve the nonlinear equations. The findings are summarized in a graphical and tabular format. The impacts of several controlling parameters such as porosity, suction, Schmidt number and volume fraction on flow pattern, thermal properties, and concentration are investigated and discussed. The streamwise and normal velocity profiles fall and those of concentration and temperature rise with increase in the values of the porosity parameter.

Magnetohydrodynamic hybrid nanofluid (Cu-Al2O3/H2O) flow along an infinitely long plate accelerated exponentially with constant species diffusion, varying heat source and under the chemical reactive, radiation absorptive influences are analysed. Non-dimensional partial differential equation system is derived from the governing nonlinear boundary layer equations. Both analytical and numerical solutions to these equations are obtained using Laplace transform approach and finite difference method. The investigation has been conducted across a broad spectrum of magnetic parameters, thermal Grashof numbers, mass Grashof numbers, radiation absorption parameters, and chemical reaction parameters. Graphical representations are used to show the implications of factors like Schmidt number, mass Grashof number, chemical reactive variable, thermal Grashof number, absorption of radiation on flow, heat, mass transfer and on their gradients as well. Velocity enhances with rising amounts of thermal and solutal buoyancy forces. Reversal tendency is noticed in situation of chemical reaction parameter and magnetic field parameter. Temperature transmission rate of hybrid nanofluids is higher than conventional nanofluids and pure fluids.

Trihybrid nanofluids exhibit superior heat transfer capabilities as compared to single or binary nanofluids. The synergistic interaction between the various types of nanoparticles results in an increased thermal conductivity as well as heat transfer rate. Trihybrid nanofluids are ideal for heat exchange applications such as solar thermal systems, power plants, heat exchangers, and electronic cooling systems. Our concern in this paper is to incorporate the artificial intelligence (AI) and numerical simulation technique to assess the thermal attributes of trihybrid structured flow over a curved geometry. The nano-composition of gold (Au), single-walled carbon nanotubes (SWCNTs) and, aluminium oxide (Al2O3) make amalgamation in the base fluid H2O to prepare the trihybrid mixture. Two methods are employed to model and analyze the governing system. The first one is Quasi-linearization method (QLM), a numerical technique used to linearize and solve non-linear differential equations. The second method is Bayesian regression neural network (BRNN), a machine learning approach that integrates Bayesian statistics with neural networks to predict outcomes. The results are compared, under limiting conditions, with the earlier ones to validate the model. For the higher curvature parameter, higher will be the velocity and lower will be the temperature in the flow regime. The AI-driven numerical simulation for trihybrid structured flows over different geometries opens new avenues in the engineering applications involving aerodynamics, biomedical devices, and industrial processes.

The purpose of the current study is to evaluate the impact of using beef Tallow methyl ester blends on the thermal parameters of diesel engine numerically utilizing Diesel-RK simulation software. The multizone combustion model is used and the governing equations are solved for each independent zone. The engine characteristics were examined under three different volumetric blends of Tallow methyl ester (10 %, 20 % and 30 %) in addition to plain diesel case for comparison. The obtained results showed slight reduction in pressure, heat release for all blends of Tallow methyl ester with respect to diesel fuel alone. The Sauter mean diameter of the droplets was increased by 1.68 %, 3.34 % and 5 % for 10 %, 20 % and 30 % Tallow methyl ester respectively. The higher tallow methyl ester ‘s cetane number is responsible for shorter ignition delay which in turn makes the combustion starts earlier. The brake specific fuel consumption increased 1.68 %, 3.34 % and 5 % for 10 %, 20 % and 30 % Tallow methyl ester respectively due to the difference of density, viscosity and energy contents. Noticeable reduction in the Bosch Smoke Number as the use of 20 % TME and 30 % Tallow methyl ester reported reduction of 13.25 % and 17.8 % while the Particulate Matter is dropped significantly by 11.1 %, 12.9 %, 18.4 % correspond to 10 %, 20 %, and 30 % percentages of Tallow methyl ester biodiesel. The plenty of oxygen quantity in Tallow methyl ester biodiesel leads to emit more Nitrogen oxides relative to diesel. Base on the results obtained, 20 % TME is best compromised blend that can recommended to be used in diesel engine without any modification of the engine. The current findings matched well with the different scientists’ results.

This work focuses on the non-linear dynamics of unsteady tri-hybrid nanofluids inside a thermally radiative, expandable or contractible cylinder, which has been a consistent subject of interest for contemporary researchers. An advanced model is formulated to address the unsteady external flowing of a conductive 50 %:50 % by volume aqueous solution of ethylene glycol-based ternary hybrid nanofluid (THNF) over a linearly stretched cylindrical structure, considering the significant applications of an anti-freeze agent in industrial, construction, nuclear, and mechanical domains. The proposed tri-hybrid nanomaterials consist of cobalt magnetite, titania, and magnesium oxide nanoparticles. The heat transfer rate is analyzed concerning viscous dissipation, Ohmic heating, and convective boundary conditions. This research examines the effects of magnetic and induced electric fields. The non-dimensional similarity model for the controlling partial differential system is derived using appropriate transformations and solved by the homotopy analysis technique (HAM) to get series solutions. In contrast to porosity and magnetic characteristics, the flow rate increases with increasing unsteadiness and electric factors. Close to the surface, the Nusselt number rises with an increasing unsteadiness parameter, but skin frictions diminishes. THNF has been shown to significantly enhance the cooling of cylindrical conduits and mechanical antifreeze agents.

The current research looks into magnetohydrodynamics Casson nanofluid flow and suction/injection implications for a nonlinearly stretched interface. To improve heat transport, joules of heat, radiation impacts and thermal stratification are used. A Darcy-Forchheimer porous media is used to conduct fluid flow. Chemical reactions involving energies of activation and solutal stratum are additionally considered. The Keller-box technique is used to solve the resulting non-linear set of ordinary differential equations. The impacts of a number of variables are examined employing diagrams of quantity, velocity, and heat. Increased assessments of porousness, Darcy-Forchheimer, and Casson fluid characteristics result in a decrease in velocity trends. For improved measurements of Lewis number and solutal fractionated factors, the intensity pattern reduces. The skin friction factor increases with increasing Casson parameter estimate. In the instance of the porous and nonlinear stretching parameters, the Nusselt number rises. For increasing levels of the Lewis number and Brownian motion factors, the Sherwood number drops. Furthermore, Nusselt number ratios are estimated with Prandtl numbers with regard to current information available, which shows remarkable consistency. For varied incorporated parameters, streamlines, heatlines, and masslines additionally displayed.

Artificial neural networks (ANNs) have a wide range of applications in science and technology. Artificial neural networks (ANNs) widely utilized in image and speech recognition, neural language processing, drug discovery, genomics and bioinformatics, Robotics and control systems, material science and energy and power system. Due to the above applications, the main focus of this article is to scrutinize the impact of inclined magnetic field on a cross nanofluid flow with slip velocity and convective boundary conditions over a variable porosity. Gold (Au) nanoparticles are suspended in base liquid blood. Thermal stratification and heat generation with joule heating impact is taken in the energy equation in order to see the heat transfer. To transform the non-linear partial differential equations (PDE's) into non-linear ordinary differential equations (ODE's) utilized the von-Karman similarity transformation parameters. For the solutions of the non-linear ODE's, the 4th- order Runge-Kutta numerical method is employed. A dataset for the employed neural network back propagated Levenberg-Marquard scheme (NN-BLMS) is generated for various estimations of the embedded parameters like Weissenberg number, magnetic parameter, angle of inclination, porosity and permeability parameters, thermal stratification parameter by utilizing the 4th-order Runge-Kutta numerical scheme. The testing, validation and training methods of NN-BLMS are utilized to scrutinize the approximate solution of cross nanofluid with slip velocity and convective boundary conditions. The performance of the proposed NN-BLMS to successfully solved the cross nanofluid model is endorsed via mean squared error, error histogram and regression analysis. Streamlines and heatlines are plotted for different parameters including in velocity and temperature equations.

Research on hybrid nanofluid flow around spinning discs has potential uses in cooling technology, microfluidics, and energy systems, among other areas. Furthermore, in recent scientific and engineering endeavors, it is becoming more crucial to take sustainability and environmental impact into account when conducting nanofluid research. Heat transfer and heat generation/absorption has been examined due to activation energy and binary chemical reaction for the magnetohydrodynamic flow of hybrid nanofluid owing to rotating disk. Also, the introduction of Casson nanofluid has been made in this analysis. Temperature and concentration both show a rising tendency for rising Ha. Stronger temperature is correlated with higher Pr, while the opposite is true. With Nb and Nt, a stronger temperature distribution is observed. The concentration field for Higher γ shows a decreasing trend. The results show the rapid change for aggregated nanoparticles as compared to non-aggregated nanoparticles. The inclusion of hybrid nanofluid improves the temperature and thermal layers heat transfer in concerning nanofluid.

Abstract In order to understand the characteristics of bio-convection and moving microorganisms in flows of magnetized Walters-B nano-liquid, we developed a model employing Riga plate with stretchy sheet. The Buongiorno phenomenon is likewise employed to describe nano-liquid motion in the Walters-B fluid. Expending correspondence transformations, the partial differential equation (PDE) control system has been transformed into an ordinary differential equation (ODE) control system. The COMSOL program is used to generate mathematical answers for non-linear equations by employing the Galerkin finite element strategy (G-FEM). Utilizing logical and graphical metrics, temperature, velocity, and microbe analysis are all studied. Various estimates of well-known physical features are taken into account while calculating nanoparticle concentrations. It is demonstrated that this model's computations directly relate the temperature field to the current Biot number and parameter of the Walters-B fluid. The temperature field is increased to increase the approximations of the current Biot number and parameter of the Walters-B fluid.

In the present study, the natural transform iterative method (NTIM) has been implemented for the solution of a fractional Zakharavo–Kuznetsov (FZK) equation. NTIM is a relatively new technique for handling non-linear fractional differential equations. The method is tested upon the two non-linear FZK equalities. The solution of the proposed technique has been compared with the existing perturbation–iteration algorithm (PIA) method and residual power series method (RPSM). From the numerical results, it is clear that the method handles non-linear differential equations very suitably and provides the results in very closed accord with the accurate solution. As a result, the NTIM approach is regarded as one of the finest analytical techniques for solving fractional-order linear and non-linear problems.

Background: The main aim of this article heat transfer in thermal engineering deals with the production, use, transformation, and transfer of thermal energy. Engineering and industrial fields including food packaging, the production of food additives, electronic cooling, microturbines, etc. Heavily rely on heat transmission. Due to its intriguing potential in industries like the production of polymers, paper, crystal glass, etc., scientists from all over the world have endeavored to investigate the effect of heat transmission on fluid flows past an expandable surface.Purpose: The use of a single-phase technique to assess Newtonian nanofluid flow along stretched surfaces with heat transfer convective models is emphasized in this research. A mathematical formulation is used to do the numerical computations for copper oxide (CuO), aluminum oxide (Al2O3), and titanium dioxide (TiO2) nanoparticles using water (H2O) as the base fluid.Formulation: The fifth-order Runge-Kutta shooting method procedure with shelling performance are used to solve non-linear ordinary differential equations with boundary conditions numerically. Researched and analyzed for changes in several parameters, plots illustrating the effects of motivated and non-motivated MHD are given to explain the physical values.Finding: Dispersion of solid items in the working fluid is reported to significantly improve thermal performance. The Biot number determines how convective the border is. With an increase in the Biot number, the fluid’s temperature drops significantly. It has been demonstrated that Copper oxide (CuO), nanoparticles are more efficient than Titanium Dioxide (TiO2) and Aluminum Oxide for thermal enhancement (Al2O3).Novelty: As far as the authors are aware, no studies have been done on the steady MHD flow and convective heat transfer of nanofluids over a nonuniform stretched surface under the influence of a heat source and viscous dissipation.

The influence of various influential factors on the flow field, temperature, and concentration variations are observed throughout the study of thermo-physical properties. The transfer of heat in fluids and thermal instability/stability are fascinating areas of study because of their vast range of applications, and physical significance in many engineering systems. This research aims to investigate and evaluate the flow characteristic, heat and concentration variations of hybrid nanofluids containing MHD natural convection flow of micropolar CuO-Ag/water in porous media across a vertically positioned plate. The flow model is treated with suction/injection at the plate’s surface, thermal radiation, heat generation and absorption, Joule heating, and viscous dissipation. The non-Fourier theory for the heat flux model is used to diminish the thermal instability. Mathematical system for the proposed model having some physical aspects results in a system of PDEs form which is restricted the boundary layer approximation is used. The PDEs model is then converted into an ODEs system using the suitable transformations. Numerical scheme RK-4 in collaboration shooting technique is used to find the best approximate results. For the validation of the employed technique, a comparison is offered from literature to confirm the dependability of the produced solution. Physical characteristics of the given solution have been studied and demonstrated against various associated influential factors. In the case of hybrid nano-structures, thermal growth is accelerated rather than in the event of nanofluid. The momentum layer thickness is more essential in hybrid nanoparticles than in nanoparticles. It’s also being looked at how crucial flow parameters affect heat transmission and skin friction.