Mohsen Saffari Pour

In the context of global warming and pollution concerns, refrigeration systems have become pivotal in energy conversion system. Within this realm, ejector types that harness renewable energy resources emerge as promising alternatives, offering a pathway towards environmentally conscious and resilient energy practices. Under specific conditions, condensation within the heat exchanger results in diverse droplet sizes at the ejector inlet, inducing homogeneous-heterogeneous condensation (HMTC) and heterogeneous condensation (HTC) phenomena. This study aims to evaluate and improve the performance of steam ejectors by investigating and optimizing the effects of homogeneous condensation (HMC), HTC, HMTC, and evaporation processes using a machine learning (ML) framework. The drone squadron optimization (DSO), Particle Swarm Optimization (PSO), and Genetic Algorithm (GA) are chosen and used in the ML framework to find the optimal droplet radius and number. Findings predict that the presence of 1018 1/kg droplets with a radius of 0.02 μm (Optimal mode) at the inlet results in a 2.6% increase in the entrainment ratio () and a 6.9% reduction in the entropy generation compared to the baseline mode. Generally, the research reveals that HTC exhibits superior performance compared to prevailing theories, leading to enhanced ejector performance.

Experimental and analytical researches have shown that the use of the bottom air-deck blasting improves fragmentation and reduces toe problems. In this research modelling of bottom air-deck blasting in a single hole, using numerical methods was taken into account. Considering the advantages of the Smoothed Particle Hydrodynamics (SPH) method, this method was used for modelling. In order to reduce the runtime of the process, the SPH–FEM coupled method was applied, using LS-DYNA software. To validate the modelling, the results of an experimental modelling of a single blast hole, in Barre granite was used. The results have shown that at the start of detonation, as the first free face is the bottom air-deck, hence, the blasting shock wave and explosive products move toward the air-deck area at a speed of 2.5 km/s and pressure on the wall of the blast hole in the air-deck area is more than the one at the starting point of detonation. Also, in conventional blasting, initial induced pressures are more than ones induced by air-deck blasting, but regarding the high attenuation of waves in conventional blasting, the applying time of pressures is very small. In bottom air-deck blasting, although the level of initial pressures are low, however, multiple impacts of blast waves in the air-deck area can transform compressive stress to tensile stress and produce higher and longer duration waves. These phenomena can contribute to an increase in the creation of fractures and improve the fragmentation at the bottom of the blast hole.

In this paper, a thermal performance assessment of traditional building constructions and configurations in various Moroccan climates is carried out. This research focuses on enhancing conventional energy efficiency of buildings by investigating the thermal behavior of single clay walls, double clay walls, simple brick walls, and double brick walls based on long-term meteorological data using TRNSYS software. The roof pitch, thermal comfort and discomfort index, and building energy consumption are considered while selecting buildings for each temperature zone. It is noticed that the double brick construction is more efficient in all climatic zones of Morocco. Thus, this material reduces the yearly energy requirement of building by 22% to 25% compared to the usual brick building. On the coldest winter days, a 30° south-facing roof raises the internal temperature by 2.5 °C compared to a horizontal roof. Temperature increases could reduce the air conditioning energy usage by 7% to 32% and overcooling hours by 12% to 21% in cities above 30° N. In addition, the findings are interesting enough to inspire individuals to implement the recommended construction design and study energy efficiency and thermal comfort in Moroccan buildings. Consequently, reducing energy consumption, mitigating climate change, and lowering greenhouse gas emissions.

Non-equilibrium phenomena and related damages have always been one of the great concerns among researchers, designers, and industry managers. In power plants, the overhaul of turbines during a pre-planned schedule includes checking, repairing, and replacing damaged parts, which always challenge industry investors with variable costs. In this study, a modified profile for the stationary cascade blades of a 200 MW steam turbine is predicted by help of the Computational Fluid Dynamics (CFD) according to a cost-saving approach for a power plant. Wet steam model is used to investigate the flow behavior between the turbine blades, due to the sonication and non-equilibrium phenomena. The numerical model based on the Eulerian-Eulerian approach accounts the turbulence caused by the presence of droplets, condensation shocks and aerodynamics. At first, such model has been carefully validated against the available experimental data. Then, the entrance edge of the blade is designed considering different shapes and sizes. The flow behavior at the entrance edge region has been fully investigated. Finally, according to the criteria for measuring the non-equilibrium flow phenomena (erosion rate, Mach number, entropy, exergy destruction and transfer of mass and heat between flow phases), a modified model for the steam turbine blade considering the economic aspects has been presented. The modified blade model exhibits 88%, 0.13% and 7% reduction in the erosion rate, entropy generation and exergy destruction, respectively. Furthermore, the application of this modified blade profile save 456$ of the total monthly maintenance costs.

The gas pressure in the main network of transmission lines is about 700 to 1000 psi (4826.33 to 6894.76 kPa), which is reduced to 250 psi (1723.69 kPa) at the entrance station of a city. This reduction process, which occurs in the regulator, causes a severe drop in gas temperature. The drop in the gas temperature produces hydrates and even causes the water vapor in the gas to freeze. As a result, there is a possibility that the passage of gas in the regulator is blocked and the gas flow is cut off. By employing heaters (indirect water heaters), the temperature of the gas entering the regulator can be preheated to eliminate the possibility of freezing in the regulator. This heater is fueled with natural gas and it operates for 24 hr a day, especially in the cold seasons. Therefore, one of the main challenges in using this type of heater is its high fuel consumption. Consequently, researchers are looking for a solution to reduce the fuel consumption (natural gas) of gas heaters. In this paper, the heat transfer and fluid flow in a heater of a natural gas pressure reduction plant, the Aliabad Power Plant (Iran), are numerically investigated using a commercial Computational Fluid Dynamics (CFD) code, ANSYS FLUENT 18.2. The considered heater consists of three parts, including (i) gas coils, (ii) a water bath (shell), and (iii) a fire tube. The indirect heat transfer process takes place between the hot liquid flow in the fire tube (combustion exhaust) and the cold liquid flow (natural gas) using the natural convection flows generated in the water bath. Numeric modeling is performed for four different gas mass flows, including 6 × 104, 8 × 104, 1 × 105, and 12 × 105 standard cubic meters per hour (or 16.67, 22.22, 27.78, and 33.33 m3/s). The results indicate that the natural gas outlet temperature achieved to a temperature higher than required. By installing a regulator on the burner, the gas consumption can be reduced, resulting in station cost savings, and also reducing the environmental impacts. The outcomes depict that the maximum possible reductions in monthly gas consumption and economic savings in the proposed system are 67,500 m3 and IRR 25 million at a gas mass flow rate of 60,000 SCMH.

In this study, the dehumidification strategy has been used to reduce the damages caused by the non-equilibrium condensation flow. In the first stage, the non-equilibrium condensation phenomenon modeling has been performed after a sensitivity grid size test, and validated by an Eulerian-Eulerian approach for the machine learning (ML) initial data. In the next step, the location of nozzle have been evaluated for the ML to predict the non- equilibrium phenomenon. Then, the output data of the numerical method have been used as the initial data for the ML method. Finally, after accurately ensuring the prediction of the ML from the behavior of the non-equilibrium condensing flow compared to the experimental data, the dehumidification technique has been linked to the ML. By help of the ML approach, a performance optimization has been carried out to reduce the presence of water droplets on different locations of the blade surface. In this way, the numerical simulations result by applying the ML have been linked and the final optimized model according to the defined parameters has been developed. It is noteworthy to mention that the objective functions are defined according to the energy of flow and the corrosion rate. The outcomes from such optimization could lead the designers to find the best location for suction dehumidification technique for the turbine blades. The machine learning has been linked to three optimization algorithms, including drone squadron optimization, particle swarm optimization, and genetic algorithm. According to the obtained results of the employed machine learning and optimization methodology, for the optimum case compared to the original case, 99%, 1%, 18%, and 90% reductions have been achieved for the erosion rate, entropy, loss of moisture, and droplet sizes, respectively. It means that, by performing such research one could study some optimization parameters and link them by artificial intelligence to investigate the best place for the suction dehumidification technique.

The current research presents a techno-economic feasibility analysis of the stand-alone hydrogen-based configurations to electrify three poor-energy islands located to the east of Canada (Pelee, Wolfe, and Saint Pierre Islands). The proposed procedure explores the possibility of various hybrid energy systems, including wind turbine, electrolyzer, hydrogen tank, diesel generator, fuel cell, supercapacitor, and converter, considering two main scenarios; Scenario I: with diesel and Scenario II: without diesel. The real-time field data of wind speed, outside air temperature, load demand, and diesel price during 8760 hr in a year have been used. The optimization results favored scenario I in Saint Pierre Island, which utilizes 133 wind turbines, 600 kg hydrogen tanks, 600 kW electrolyzer, 200 kW diesel generator, 100 kW fuel cell, 363 701 supercapacitor units, and 252 kW converter. This combination has $0.68 M (16%) and $2 M (36%) lower the net present cost (NPC), as well as $0.059/kWh (19%) and $0.175/kWh (36%) lower the levelized cost of electricity than scenario I in Pelee Island and Wolfe Island, respectively. Among solutions from scenario I, the cleanest case is found in Saint Pierre Island by having four- and three-times lower emissions than options in Wolfe Island and Pelee Island, respectively. The economic indicators are highly dependent on the capital cost fluctuations of supercapacitor and wind turbines than other components. Sensitivity analysis highlighted that the lowest values of the NPC are seen under the inflation rate of 2% within 10 to 16 m/s wind speed and 14% inflation rate within 12 to 15 m/s wind speed. The effects of timestep fluctuation revealed that optimizing solutions within samples in intervals greater than 30 min is recommended.

In this paper, the thermal performance improvements of a heat removal system like an electronic system have been analyzed. The studied case is a horizontal channel in which two partially inclined baffles are attached with variable height and number. The channel is crossed by a forced convective flow of a cooling fluid (air). This numerical work evaluates the influences of the height and number of the baffles on the enhancement of the heat transfer rate. The mathematical model of this system is composed of nonlinear partial equations that the analytical solution for them is very complex, hence the need for numerical analysis is mandatory with the aid of a finite volume method. Accordingly, The numerical results are presented in axial and transverse velocity, temperature, local and average Nusselt number, local friction coefficient, pressure drop, heat transfer rate, and turbulence kinetic energy. The results revealed that it is possible to improve the thermal performance of the considered system by adopting designs that allow the maximum heat transfer rate with the minimum energy loss. In addition, results show that at the lowest Reynolds number (Re = 10,000), as the height of baffles rises from 0.01 to 0.03 m (growth by 200%), the heat transfer rate augments about 59.09%. Moreover, at the highest evaluated Reynolds number (Re = 87,300), by increasing the height of baffles up to 200%, the heat transfer rate increases by approximately 50.53%. Furthermore, employing a higher number of baffles leads to more heat transfer rates and a significant pressure drop.

In this numerical work, heat transfer characteristics of humid air in a rectangular channel as solar air heater equipped with V-shaped ribs has been investigated. The impacts of geometrical parameters of proposed ribs such as height, pitch, and angle relative to air flow direction, as well as relative humidity and Reynolds number of inlet humid air on thermal performance of proposed solar air heater have been evaluated. The numerical results have been achieved using commercial Computational Fluid Dynamics (CFD) code, ANSYS FLUENT 18.2, which works based on finite volume method. Outcomes shows that, over a wide range of operating conditions, utilizing ribs cause thermal boundary layer to separate and reattach, and eventually enhance heat transfer rate. Increasing the rib angle produces stronger secondary flows, leading to higher local velocities and greater heat transfer rate. Moreover, increasing the relative humidity of inlet air from 0% to 50% leads to improve heat transfer by up to 6%. As Reynolds number increases from 4000 to 12,000, average Nusselt number rises by 7.3% and 31.4% for rib pitches of 6 and 16 mm, respectively. The results demonstrate how thermal performance of a solar air heater can be improved by utilizing V-shaped ribs.

Due to the high enthalpy of fusion in water, ice storage systems are known as one of the best cold thermal energy storage systems. The phase change material used in these systems is water, thus it is inexpensive, accessible, and completely eco-friendly. However, despite the numerous advantages of these systems, the phase change process in them is time-consuming and this leads to difficulties in their practical application. To solve this problem, the addition of nanomaterials can be helpful. This study aims to investigate the compound heat transfer enhancement of a cylindrical-shaped unit equipped with double helically coiled coolant tubes using connecting plates and nano additives as heat transfer augmentation methods. Complex three-dimensional numerical simulations are carried out here to assess the best heat exchanger material as well as the impact of various nanoparticle types, including alumina, copper oxide, and titania, and their concentrations in the PCM side of the ice storage unit. The influence of these parameters is discussed on the charging rate and the temperature evolution factor in these systems. The results suggest that using nano additives, as well as the connecting plates, together is a promising way to enhance the solidification rate by up to 29.9%.

Nowadays, nanoparticles have been widely applied in liquids due to their great impact on the growth rate of heat transfer as well as the solutions for the problems raised from the use of particles larger than nano in various currents. Therefore, in this article, an attempt has been made to study the research carried out in the field of forced heat transfer of nanofluids inside channels and pipes. In this way, the authors are reviewing articles starting from 2018 for channels and 2017 for tubes/pipes. All the articles that are in the above category have been studied from different viewpoints. In this article, first, the type of flow and the relations used in this field are introduced and by comparing the published articles in terms of methodology, type and size of nanoparticles, volumetric ratios of nanoparticles, flow conditions, etc., so that the effect of these parameters can be studied on heat transfer. The following is a statistical study of articles in this field, which includes all articles published from the beginning to the present, which have dealt with this issue in theory, numerical and experimental. As a result, it becomes clear that the special geometric properties of channels and pipes, the insertion of obstacles in the flow path with special conditions and characteristics, as well as the boundary conditions defined in recent studies have considerable influence on the growth of heat transfer rate and the improvement of system efficiency.

In this paper, the Magneto hydrodynamics (MHD) mixed convection and entropy analysis by introducing a power law hybrid nanofluid in a wavy elbow-shaped cavity with a quarter circle hot block and a rotating cylinder is studied numerically. A Galerkin finite element method (GFEM) is employed to study a rotating adiabatic cylinder, which is surrounded by an elbow-shape cavity. This cavity is bounded to a wavy wall, which is placed at the top. All walls are isothermal except one horizontal wall which is set to be at a cold condition. The heat source is located in the lower corner of this specific geometry. To investigate the thermal and hydrodynamics behavior of such specific cavity the Nusselt (Nu) numbers are compared. Moreover, a comparison is devoted for different aspect ratios, the Hartmann number, the nanofluid volume fraction and the power law index for the elbow-shaped cavity. Results proved that the Nu number increases via increasing the power law index. It is also inferred that the clockwise rotation, enhanced the heat transfer rate. In addition, it is depicted that by increasing the aspect ratio (AR) the heat transfer rate increases. Also, the entropy generation is fully investigated for the current geometry for the above-mentioned parameters.

In this study according to the challenges of the power generation industry and condensing losses of wet steam flow, the strategy of Nano-droplets injection in nucleation zone is used. The strategy as such have been adopted to reduce the condensing losses of the flow and increase the efficient energy of the steam turbine. In the first step, after performing the sensitivity analysis on the computational domain of the non-equilibrium condensation model, the results are validated with the experimental data. Also, the SST k-ω turbulence model is utilized to simulate the latency created by the presence of Nano-droplets in the created domain. In the second step, the measurement criterion for injection effects in different locations of the nucleation zone is defined as efficient energy. This energy for the steam turbine are calculated as the energy of flow between the cascade blade, which it has the lowest wet losses of liquid phase and the highest temperature, velocity and internal energy. Finally, based on the Modified case, the efficient energy parameters have been presented, which result in a decrease of approximately 45% 27.5%, 21.4% 44% and 18%, for the condensation losses, droplets radius size, liquid mass fraction, the erosion rate ratio and wetness losses, respectively. Additionally an increasing trend of 18.25% and 0.2% for the efficient energy and Mach number has been observed.

Variable speed wind turbines are commonly used as wind power generation systems because of their lower maintenance cost and flexible speed control. The optimum output power for a wind turbine can be extracted using maximum power point tracking (MPPT) strategies. However, unpredictable parameters, such as wind speed and air density could affect the accuracy of the MPPT methods, especially during the wind speed small oscillations. In this paper, in a permanent magnet synchronous generator (PMSG), the MPPT is implemented by determining the uncertainty of the unpredictable parameters using the extended Kalman filter (EKF). Also, the generator speed is controlled by employing a fuzzy logic control (FLC) system. This study aims at minimizing the effects of unpredictable parameters on the MPPT of the PMSG system. The simulation results represent an improvement in MPPT accuracy and output power efficiency.

In the present work, a parabolic trough solar (PTC) collector with inner helical axial fins as swirl generator or turbulator is considered and analyzed numerically. The three-dimensional numerical simulations have been done by finite volume method (FVM) using a commercial CFD code, ANSYS FLUENT 18.2. The spatial discretization of mass, momentum, energy equations, and turbulence kinetic energy has been obtained by a second-order upwind scheme. To compute gradients, Green-Gauss cell-based method has been employed. This work consists of two sections where, first, four various geometries are appraised, and in the following, the selected schematic of the collector from the previous part is selected, and four various pitches of inner helical fins including 250, 500, 750 and 1000 mm are studied. All the numerical results are obtained by utilizing the FVM. Results show that the thermal performance improvement by 23.1% could be achieved by using one of the proposed innovative parabolic trough solar collectors compare to the simple one. Additionally, the minimum and maximum thermal performance improvement (compare to the case without fins) belong to the case with P = 250 mm by 14.1% and, to the case with P = 1000 mm by 21.53%, respectively.

This paper studied the cooling performance of a hot electronic chip using nanofluids (NF) mixed convection, implementing Buongiorno’s model of the NF simulation. The NF were assumed water-Al2O3 nanoparticles (NP) in the range of 0 to 4% of volume concentration. Six different problems of the combinations of three internal hot blocks, including triangular, square, and circular geometries, and two porous media, including sand and compact metallic powder, were numerically solved. To discretize the governing equations, a finite control volume method was applied. As most of the proposed correlations for the thermophysical properties of the NF were inaccurate, especially for thermal conductivity, a new predictive correlation was proposed using the multi-variable regression method with acceptable accuracy. It was found that the cooling performance improved with any increase in the NP loading. A higher nanoparticle concentration yielded better cooling characteristics, which was 11.93% for 4% volume. The sand porous medium also yielded a much higher value of the normalized Nusselt number (Nu) compared to the other medium. The entropy generation (EG) enhancement was maximum for the triangular hot block in a sand porous cavity.

Thermal energy storage units conventionally have the drawback of slow charging response. Thus, heat transfer enhancement techniques are required to reduce charging time. Using nanoadditives is a promising approach to enhance the heat transfer and energy storage response time of materials that store heat by undergoing a reversible phase change, so-called phase change materials. In the present study, a combination of such materials enhanced with the addition of nanometer-scale graphene oxide particles (called nano-enhanced phase change materials) and a layer of a copper foam is proposed to improve the thermal performance of a shell-and-tube latent heat thermal energy storage (LHTES) unit filled with capric acid. Both graphene oxide and copper nanoparticles were tested as the nanometer-scale additives. A geometrically nonuniform layer of copper foam was placed over the hot tube inside the unit. The metal foam layer can improve heat transfer with an increase of the composite thermal conductivity. However, it suppressed the natural convection flows and could reduce heat transfer in the molten regions. Thus, a metal foam layer with a nonuniform shape can maximize thermal conductivity in conduction-dominant regions and minimize its adverse impacts on natural convection flows. The heat transfer was modeled using partial differential equations for conservations of momentum and heat. The finite element method was used to solve the partial differential equations. A backward differential formula was used to control the accuracy and convergence of the solution automatically. Mesh adaptation was applied to increase the mesh resolution at the interface between phases and improve the quality and stability of the solution. The impact of the eccentricity and porosity of the metal foam layer and the volume fraction of nanoparticles on the energy storage and the thermal performance of the LHTES unit was addressed. The layer of the metal foam notably improves the response time of the LHTES unit, and a 10% eccentricity of the porous layer toward the bottom improved the response time of the LHTES unit by 50%. The presence of nanoadditives could reduce the response time (melting time) of the LHTES unit by 12%, and copper nanoparticles were slightly better than graphene oxide particles in terms of heat transfer enhancement. The design parameters of the eccentricity, porosity, and volume fraction of nanoparticles had minimal impact on the thermal energy storage capacity of the LHTES unit, while their impact on the melting time (response time) was significant. Thus, a combination of the enhancement method could practically reduce the thermal charging time of an LHTES unit without a significant increase in its size.

Thermal energy storage is a technique that has the potential to contribute to future energy grids to reduce fluctuations in supply from renewable energy sources. The principle of energy storage is to drive an endothermic phase change when excess energy is available and to allow the phase change to reverse and release heat when energy demand exceeds supply. Unwanted charge leakage and low heat transfer rates can limit the effectiveness of the units, but both of these problems can be mitigated by incorporating a metal foam into the design of the storage unit. This study demonstrates the benefits of adding copper foam into a thermal energy storage unit based on capric acid enhanced by copper nanoparticles. The volume fraction of nanoparticles and the location and porosity of the foam were optimized using the Taguchi approach to minimize the charge leakage expected from simulations. Placing the foam layer at the bottom of the unit with the maximum possible height and minimum porosity led to the lowest charge time. The optimum concentration of nanoparticles was found to be 4 vol.%, while the maximu possible concentration was 6 vol.%. The use of an optimized design of the enclosure and the optimum fraction of nanoparticles led to a predicted charging time for the unit that was approximately 58% shorter than that of the worst design. A sensitivity analysis shows that the height of the foam layer and its porosity are the dominant variables, and the location of the porous layer and volume fraction of nanoparticles are of secondary importance. Therefore, a well-designed location and size of a metal foam layer could be used to improve the charging speed of thermal energy storage units significantly. In such designs, the porosity and the placement-location of the foam should be considered more strongly than other factors.

Building energy assessment is essential to accomplish the sustainable energy targets of new and present buildings. Retrofitting of the existing buildings by assessing them through energy models is the most prominent method. Studies revealed that there is still blank information about the building stocks, and these affect the valuation of building energy efficiency policies. Literature also recommends that the existing energy models are too complex and unreliable to predict the energy use. Reliability of such energy models would improve through a better alignment of the input parameters and the model assumptions. The authors hypothesized that the reliability of models would be improved through identification of the most relevant energy use parameters for the building stocks in different regions and models. One of the most commonly accepted methods for detecting the most dominant input parameters is sensitivity analysis, though its shortcomings include the need for a large number of data samples and long computing time. In this research, the Energy, Carbon, and Cost Assessment for Buildings Stocks (ECCABS) model is adopted to identify the most important parameters of the presented model. The research team uses the model that has been validated by studies conducted for the UK building stock. Moreover, by assessing the feasibility study with the stepwise regression to identify the significant input parameters have been discussed. Results show that stepwise regression method could produce the same results compared to sensitivity analysis. This paper also indicates that stepwise regression is considerably faster and less computationally intensive compared to common sensitivity analysis methods.

This paper investigates the cooling performance of nanofluid (NF) mixed convection in a porous I-shaped electronic chip with an internal triangular hot block using Buongiorno’s two-phase model. This type of cavity and hot block geometry has not been studied formerly. The NF was assumed to be a mixture of water and CuO nanoparticles (NP) up to 4% of volume concentration. As most published mathematical models for the thermal conductivity of NF give inaccurate predictions, a new predictive correlation for effective thermal conductivity was also developed with a high accuracy compared to the experimental data. The results showed that any increase in the NP volume concentration enhances the average Nusselt number (Nu¯¯¯¯¯) and the normalized entropy generation, and reduces the thermal performance of the cavity in all orientations of the hot block. The maximum enhancement in cooling performance was 17.75% and occurred in the right-oriented hot block in the sand-based porous cavity. Furthermore, adding the NP to the base fluid leads to a more capable cooling system and enhances the irreversibility of the process.

The application of incinerators for the municipal solid waste (MSW) is growing due to the ability of such instruments to produce energy and, more specifically, reduce waste volume. In this paper, a numerical simulation of the combustion process with the help of the computational fluid dynamics (CFD) inside a portable (mobile) incinerator has been proposed. Such work is done to investigate the most critical parameters for a reliable design of a domestic portable incinerator, which is suitable for the Iranian food and waste culture. An old design of a simple incinerator has been used to apply the natural gas (NG), one of the available cheap fossil fuels in Iran. After that, the waste height, place of the primary burner, and the flow rate of the cooling air inside the incinerator, as the main parameters of the design, are investigated. A validation is also performed for the mesh quality test and the occurrence of the chemical reactions near the burner of the incinerator. Results proved that the numerical results have less than 5% error compared to the previous experimental and numerical approaches. In addition, results show that by moving the primary burner into the secondary chamber of the incinerator, the temperature and the heating ability of the incinerator could be affected dramatically. Moreover, it has been found that by increasing the flow rate of the cooling air inside the incinerator to some extent, the combustion process is improved and, on the other hand, by introducing more cooling air, the evacuation of the hazardous gases from the exhaust is also improved.

In this research, it is investigated to numerically evaluate the performance of a polymer electrolyte membrane fuel cell (PEMFC). The performance is investigated through the nonuniformity gradient loading at the catalyst layer (CL) of the considered PEMFC. Computational fluid dynamics is used to simulate a 2D domain in which a steady‐state laminar compressible flow in two‐phase for the PEMFC has been considered. In this case, a particular nonuniform variation inside the CL along the channel is assumed. The nonuniform gradient is created using a nonisothermal domain to predict the flooding effects on the performance of the PEMFC. The computational domain is considered as the cathode of PEMFC, which is divided into three regions: a gas channel, a gas diffusion layer, and a CL. The loading variation inside the catalyst is defined as a constant slope along the channel. In order to find the optimum slope, different slope angles are analyzed. The results point out that the nonuniform loading distribution of the catalyst (platinum) along the channel could improve the fuel cell performance up to 1.6% and 5% for power density and voltage generation, respectively. It is inferred that it is better to use more catalyst in the final section of the channel if the performance is the main concern.

The present investigation addressed the entropy generation, fluid flow, and heat transfer regarding Cu-Al 2 O 3 -water hybrid nanofluids into a complex shape enclosure containing a hot-half partition were addressed. The sidewalls of the enclosure are made of wavy walls including cold isothermal temperature while the upper and lower surfaces remain insulated. The governing equations toward conservation of mass, momentum, and energy were introduced into the form of partial differential equations. The second law of thermodynamic was written for the friction and thermal entropy productions as a function of velocity and temperatures. The governing equations occurred molded into a non-dimensional pattern and explained through the finite element method. Outcomes were investigated for Cu-water, Al 2 O 3 -water, and Cu-Al 2 O 3 -water nanofluids to address the effect of using composite nanoparticles toward the flow and temperature patterns and entropy generation. Findings show that using hybrid nanofluid improves the Nusselt number compared to simple nanofluids. In the case of low Rayleigh numbers, such enhancement is more evident. Changing the geometrical aspects of the cavity induces different effects toward the entropy generation and Bejan number. Generally, the global entropy generation for Cu-Al 2 O 3 -water hybrid nanofluid takes places between the entropy generation values regarding Cu-water and Al 2 O 3 -water nanofluids.

The mixed convection two-phase flow and heat transfer of nanofluids were addressed within a wavy wall enclosure containing a solid rotating cylinder. The annulus area between the cylinder and the enclosure was filled with water-alumina nanofluid. Buongiorno’s model was applied to assess the local distribution of nanoparticles in the host fluid. The governing equations for the mass conservation of nanofluid, nanoparticles, and energy conservation in the nanofluid and the rotating cylinder were carried out and converted to a non-dimensional pattern. The finite element technique was utilized for solving the equations numerically. The influence of the undulations, Richardson number, the volume fraction of nanoparticles, rotation direction, and the size of the rotating cylinder were examined on the streamlines, heat transfer rate, and the distribution of nanoparticles. The Brownian motion and thermophoresis forces induced a notable distribution of nanoparticles in the enclosure. The best heat transfer rate was observed for 3% volume fraction of alumina nanoparticles. The optimum number of undulations for the best heat transfer rate depends on the rotation direction of the cylinder. In the case of counterclockwise rotation of the cylinder, a single undulation leads to the best heat transfer rate for nanoparticles volume fraction about 3%. The increase of undulations number traps more nanoparticles near the wavy surface.

In this paper, the thermal and hydrodynamic characteristics of a suspension with water-Nano-Encapsulated Phase Change Material (NEPCM) in an annulus of a porous eccentric horizontal cylinder are investigated. The NEPCM particles have a core-shell structure and stability suspended in water. Hence, the particles, along with the liquid, could freely circulate inside the annuli of the horizontal cylinder due to the buoyancy forces. The cores of these particles are made from a Phase Change Material (PCM). Moreover, such cores are in a continuous exchange of heat transfer between the solid and liquid phases. The heat transfer is acting in a combination of absorption, storage, and release mechanisms. The governing equations for the fluid motions and conservation of energy could be written in partial differential forms and by using the appropriate non-dimensional variables converted into non-dimensional ones. Then, the numerical approach is applied by implementing the finite element method (FEM) to solve such equations iteratively. The impact of various non-dimensional parameters including the fusion temperature, Stefan number, Rayleigh number, Darcy number, the volume fraction of nanoparticles, and eccentricity of the inner cylinder is addressed on the flow and heat transfer. It is observed that the most favourable fusion temperature ranges for the maximum heat transfer rate vary as a function of the Rayleigh number. In addition, the heat transfer rate can be enhanced by applying the phase change core of nanoparticles.

The present paper aims to investigate the influence of perforated membrane geometry on the performance of biosensors. For this purpose, a 2-D axisymmetric model of an amperometric biosensor is analyzed. The governing equations describing the reaction-diffusion equations containing a nonlinear term related to the Michaelis–Menten kinetics of the enzymatic reaction are introduced. The partial differential governing equations, along with the boundary conditions, are first non-dimensionalized by using appropriate dimensionless variables and then solved in a non-uniform unstructured grid by employing the Galerkin Finite Element Method. To examine the impact of the hole-geometry of the perforated membrane, seven different geometries—including cylindrical, upward circular cone, downward circular cone, upward paraboloid, downward paraboloid, upward concave paraboloid, and downward concave paraboloid—are studied. Moreover, the effects of the perforation level of the perforated membrane, the filling level of the enzyme on the transient and steady-state current of the biosensor, and the half-time response are presented. The results of the simulations show that the transient and steady-state current of the biosensor are affected by the geometry dramatically. Thus, the sensitivity of the biosensor can be influenced by different hole-geometries. The minimum and maximum output current can be obtained from the cylindrical and upward concave paraboloid holes. On the other hand, the least half-time response of the biosensor can be obtained in the cylindrical geometry.

In this research, a numerical investigation is done on the effect of employing the new combined vortex generators, the twisted tape turbulator and Al2O3-H2O nanofluid as the involved base fluid. Such study is carried out on the behavior of the heat transfer rate and the pressure drop of a double pipe heat exchanger. Accordingly, the response surface methodology (RSM) grounded on the central composite design (CCD) is used for acquiring the optimized geometry of the combined vortex generator and twisted tape turbulator. In order to have the maximum Nusselt number and minimum friction factor, twenty cases with different pitches ratio (, angles(°)and Reynolds numbers (Re = 5000-20000 are examined. The Results show that the pitch ratio has a predominant effect on the Nusselt number and the friction factor, which causes an efficiency increase up to five times compared to the original one. In addition, by decreasing the angle of the vortex generators in the new combined turbulator, both Nusselt number and the friction factor are increased.

This research investigates a numerical simulation of swirling turbulent non-premixed combustion. The effects on the combustion characteristics are examined with three turbulence models: namely the Reynolds stress model, spectral turbulence analysis and Re-Normalization Group. In addition, the P-1 and discrete ordinate (DO) models are used to simulate the radiative heat transfer in this model. The governing equations associated with the required boundary conditions are solved using the numerical model. The accuracy of this model is validated with published experimental data and the comparison elucidates that there is a reasonable agreement between the obtained values from this model and corresponding experimental quantities. Among different models proposed in this research, the Reynolds stress model with the probability density functions approach is more accurate (nearly up to 50%) than other turbulent models for a swirling flow field. Regarding the effect of radiative heat transfer model, it is observed that the discrete ordinate model is more precise than the P-1 model in anticipating the experimental behavior. This model is able to simulate the subcritical nature of the isothermal flow as well as the size and shape of the internal recirculation induced by the swirl due to combustion.

In this numerical study, the variations in the surface area of the cooling channels in a solid oxide fuel cell with different cross sections and multi-walled carbon nanotubes oil/MWCNT nanofluid volume fractions are considered. Rectangular, trapezoidal and elliptical cross sections, and nanofluid volume fractions of 0–6% for the fluid are chosen as the studied parameters as well as the mass flow rates. In this research, a 3D model is developed by the finite volume method using the computational fluid dynamics (CFD). Then, the flow field and the heat transfer rate are predicted. The results show that the dissipated heat in the fuel cell is dependent on the mass flow rate of the fluid. That increased heat increases the heat transfer rate. The presence of the solid particles can also reinforce the heat conduction of the coolant fluid and consequently improve the heat transfer performance. The pumping power is maximum for the highest mass flow rate and the highest solid nanoparticle volume fractions. Additionally, the pumping power is dependent on the route in which the sections with lowest momentum changes and lowest pressure drops have the least amount of the pumping power. The ratio of the dissipated heat by the nanofluid over the base fluid is compared to a pressure drop. The movement of flow with the lower mass flow rates will result in penetrations of the thermal boundary layers into different flow regions, which can increase the optimum temperature in the solid part of the fuel cell. By increasing the mass flow rate of the fluid passing through the channels from 0.002 to 0.004 kg s−1, the maximum temperature is decreased by 6.13, 3.34 and 6.35% for rectangular, trapezoidal and elliptical channels, respectively.

In this paper, we present a numerical simulation of a laminar, steady and Newtonian flow of f-graphene nanoplatelet/water nanofluid in a new microchannel design with factors for increasing heat transfer such as presence of ribs, curves to enable satisfactory fluid mixing and changing fluid course at the inlet and exit sections. The results of this study show that Nusselt number is dependent on nanoparticles concentration, inlet geometry and Reynolds number. As the nanofluid concentration increases from 0 to 0.1% and Reynolds number from 50 to 1000, the Nusselt number enhances nearly up to 3% for increase in fluid concentration and averagely from 15.45 to 54.1 and from 14.5 to 55.9 for geometry with and without rectangular rib, respectively. The presence of ribs in the middle section of microchannel and curves close to hot walls causes a complete mixing of the fluid in different zones. When the nanoparticles concentration is increased, the pressure drop and velocity gradient will become higher. An increased concentration of nanoparticles in contribution with higher Reynolds numbers only increases the fraction factor slightly. (The fraction factor increases nearly 37% and 35% for Re = 50 and 1000, respectively.) The highest uniform temperature distribution can be found in the first zones of fluid in the microchannel and by further movement of fluid toward exit section, because of decreasing difference between surface and fluid temperature, the growth of temperature boundary layer increases and results in non-uniformity in temperature distribution in microchannel and cooling fluid. With decrease in the concentration from 0 to 0.1%, the average outlet temperature and FOM decrease nearby 0.62% and 6.15, respectively.

High mountains and cold climate in the north-west of Iran are critical factors for the design of optimized District Heating (DH) systems and energy-efficient buildings. It is essential to consider the Life Cycle Cost (LCC) that includes all costs, such as initial investment and operating costs, for designing an optimum DH system. Moreover, considering climate change for accurately predicting the required heating load is also necessary. In this research, a general optimization is carried out for the first time with the aim of a new design concept of a DH system according to a LCC, while considering all-involved parameters. This optimized design is based on various parameters such as ceiling and wall insulation thicknesses, depth of buried water and heating supply pipes, pipe insulation thickness, and boiler outlet temperature. In order to consider the future weather projection, the mentioned parameters are compared with and without climate change effects in a thirty-year period. The location selection was based on the potential of the region for such a system together with the harsh condition of the area to transport the common fossil fuel to the residential buildings. The obtained results show that insulation of walls is more thermally efficient than a roof with the same area in the selected case. In this case, polyurethane is the best material, which can cause a reduction of 59% in the heating load and, consequently, 2332 tons of CO2 emission annually. The most and the least investment payback periods are associated with the polyurethane and the glass wool insulation materials with the amounts of seven and one years. For the general optimization of the DH system, the Particle Swarm Optimization (PSO) method with a constriction coefficient was chosen. The results showed that the optimal thickness of the polyurethane layer for the thermal insulation of the building exterior walls is about 14 cm and the optimal outlet temperature of the boiler is about 95 °C. It can be also concluded that the optimal depth for the buried pipes is between 1.5 to 3 m underground. In addition, for the pipe with elastomeric insulation layer, the thickness of 2 cm is the optimal choice.

It is well known that the use of photovoltaic (PV) systems helps to preserve the environment, produce lower levels of greenhouse gases (GHGs), and reduce global warming, however, whether it is economically profitable for customers or not is highly debatable. This paper aims to address this issue. To be comprehensive, three different types of buildings are considered as case studies. Then, these three buildings are modeled in EnergyPlus to determine the rate of energy consumption. Afterward, comparisons of various solar system sizes based on economic parameters such as the internal rate of return, the net present value, payback period and profitability indexing for various-sized PV systems are carried out. The results show that by the demand charge tariffs, using PV systems has no economic justification. It has been shown that even with neglecting further costs of the PV system like maintenance, by demand charge tariffs, it is not economically beneficial for customers to use the PV systems. Profitability index of all three buildings with various PV power systems is between 0.2 to 0.8, which are by no means is desirable. Moreover, it was found that bigger solar systems are less cost-effective in the presence of demand charges.

In this paper, a new method is proposed for motion vector steganalysis using the entropy value and its combination with the features of the optimized motion vector. In this method, the entropy of blocks is calculated to determine their texture and the precision of their motion vectors. Then, by using a fuzzy cluster, the blocks are clustered into the blocks with high and low texture, while the membership function of each block to a high texture class indicates the texture of that block. These membership functions are used to weight the effective features that are extracted by reconstructing the motion estimation equations. Characteristics of the results indicate that the use of entropy and the irregularity of each block increases the precision of the final video classification into cover and stego classes.