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Background Concentrated solar energy systems use mirrors to focus a lot of light in one receiver. When focused light is converted to heat can drive a steam turbine connected to a power generator and electricity is generated. The purpose of this research is to analyze a small-scale industrial waste heat assisted solar tower power plant. Method The thermal performance of the system has been modelled based on the transient heat transfer analysis of the storage tank and a boiling heat transfer modeling of steam generator. Performance parameters such as working fluid temperature at the exit of components, hourly power output, as well as thermal efficiency of steam cycle has been computed. Moreover, in order to increase the efficiency of the system a CFU U-tube heat exchanger was selected and cooled using nanofluid. Findings A 16.6 kW constant power output was computed for 8760 hour of simulation time, and 19% thermal efficiency of the steam cycle is computed in this analysis. Moreover, using nanofluid in the condenser instead of water can improve heat transfer in the heat exchanger. The use of nanofluid also leads to lower temperature of liquid leaving the condenser, which increases the efficiency of the solar system.

Heterogeneous combustion in a diesel engine is noisier, uncontrolled and more polluting. This can be achieved with a strategic approach of a reactivity-controlled compression ignition (RCCI) mode engine that operates with low and high reactive fuel combinations. In the present work, a diesel engine is operated in RCCI mode with gaseous fuels viz. CNG as a primary fuel and a blend of diesel and Karanja biodiesel (BD20) as pilot fuel. This research aims to determine the operating limits of CNG fuel for less noisy combustion and clean exhaust. Further, relative air-fuel ratio (λ), cycle to cycle variations, combustion noise and emissions were studied for full load operation. The CRDI engine is optimized for diesel operation with a split injection strategy. The knock limits for CNG as the primary fuel are obtained. The combustion noise increases at a higher energy share by CNG. Also, higher values of HC and CO emissions are observed. This may be due to higher energy share values, flame speed and octane number of CNG fuel. Further, NOx emissions and smoke are decreased. The CNG induction of 10 ms with 90% ES can be noted as a knock limit for 3.5 kW power. The highest BTHE of 24.2% and least BSFC 0.3 kg/kWhr reported by 60%ES of LRF is better than diesel and KBD20 fuel. An optimum 60% energy share of CNG is observed for clean combustion and emissions strategy using the RCCI mode of a modified diesel engine.

Background Solar towers use heliostat to direct a lot of sunlight into a receiver. When concentrated solar radiation is converted to heat, it can drive a steam turbine connected to a power generator, which generates electricity. The purpose of this research is to design and analysis of a solar power plant in the climatic condition of Jeddah, Saudi Arabia. Method Both TRANSYS and THERMO FLEX software are applied for such purpose. The intended power plant is composed of two sections of a solar cycle with molten salt as working fluid and a Rankine cycle with working fluid of water for power generation. COMSOL software is applied to simulate the preheater heat exchangers. Results The results of this study indicated that the solar power plant generates the most electricity during June and July. The efficiency during these two months is 25% for molten salt nanofluid and 24% for molten salt. In addition, the use of molten salt nanofluid can improve the heat transfer in the solar receiver and produce more electricity in the power plant compared to the use of molten salt. Moreover, the use of two preheaters instead of one increases the efficiency of the cycle by up to 3%.

Background Green energy market will contribute to three fifth of the world's electric power generation and two fifths of the fuel market by the mid of the present century. The annual transient thermal performance simulation of a solar tower power plant with parallel heat exchanger is performed. Method The heat transfer process for the two tanks is performed in which a heat loss from the tanks is considered. Two-phase heat transfer analysis at the heat exchanger is studied. The hourly reflected radiation is determined from DNI data. Nanofluid coolants are used for the flat-plate solar collector. Findings It is found that the temperature profile of the melted salt at the exit of the receiver fluctuates with higher frequency. The appropriate performance of the solar collector using SiO2 dispersed nanoparticles in water, is also provided. GO-DW mono nanofluid shows a better performance; however, GO/SiO2-DW hybrid nanofluid has more cost-efficiency.

In order to determine the effect of the divergent nozzle length on the single-hose nozzle geometry, the computational couple simulation approach was employed. Furthermore, a model was successfully provided for the two-way exchange of mass, momentum, and energy between two phases. The energy that was exchanged between two involved phases, the solid dry ice particle and a working medium of compressible air-fluid, was also obtained. The model was then coupled with the acoustic programming code solved using the Mump solver. The result revealed that the most extended divergent length showed the highest flow velocity across the nozzle cavity and induced the lowest turbulence flow. Thus, the acoustic sound pressure level was reduced. The shortest divergent nozzle length, equal to 200 mm, produced the highest sound pressure level equal to 85 dBA within the frequency range of 1000 to 1200 Hz. It also produced an average maximum of sound power level, which is 100 dB, across all frequency ranges. Therefore, this study is highly essential since the characteristics of the gas-particle flow within a nozzle cavity provide a deeper understanding of the multiphase flow in turbine and jet engine flow analysis.

Composite materials inherently exhibit scatter in their basic characteristics such as the mechanical properties of constituent materials, fibers orientations, ply thicknesses, and applied loads. The uncertainties present in the basic parameters are available, in most cases, in the form of ranges or intervals. The use of the existing deterministic failure theories, which do not consider the observed variabilities in the input parameters, leads to poor failure assessment of composite materials. Several probabilistic failure models have been proposed in the past few decades. However, the probabilistic methods require a knowledge of the probability distributions of the basic variables which are not available in most practical systems. This work, for the first time, presents an interval-based failure analysis of composite materials using the truncation-based interval analysis and the universal gray system theory. These methods require only the lower and upper bounds of the uncertain parameters which are available in most practical systems. The application of the proposed interval-based failure models is demonstrated by considering two types of graphite/epoxy laminates: [0/±45/90] S and [0/90]2. This work shows that more realistic and meaningful failure assessment can be made using the universal gray system theory and the truncation-based interval analysis compared to the deterministic failure analysis.

The present study was numerically inquired the heat transfer performance and fluid flow characteristic of a helical micro double-tube heat exchanger (HMDTHX) using the finite volume method. The tube length was considered to be constantly equal to 30 mm, and 12 different configurations were modeled by changing in turn number and pitch length (P) for Reynolds numbers of 50, 100, 150, and 200. The findings indicated that the heat transfer would enhance by applying any helix angle in the straight tube. However, it had an optimum point which varied by Reynolds number (Re). Rising Re caused overall heat transfer coefficient (OHTC), pressure drop, and pumping power augment for all cases. Increasing P in overall reduced OHTC, pressure drop, and pumping power which had different maximum points between P = 0.5 to 3. Maximum overall heat transfer coefficient (OHTC) enhancement was equal to 45% for Re = 200 and P = 2. Also, maximum effectiveness was 11.5% for P = 2 and Re = 200. Moreover, a 42% maximum increment was achieved for pressure drop, pumping power, and friction factor at Re = 200 and P = 2. Shear stress for Re = 100 to 200 showed that the values are almost the same for P = 0.5 and 1. Then by increasing P, the shear stress decreases. While, for Re = 50, a maximum is seen at P = 2. The temperature distribution was indicated that the maximum temperature of the straight tube and helical tube are the same, but the difference is in the average temperature, which was 3.2 K between straight and helical tubes. Finally, by investigating the velocity contour, it was determined that a secondary flow through the HMDTHX, affected by centrifugal force, was existed, enhancing the fluid flow turbulency and heat transfer rate.

PTSCs (parabolic trough solar collectors) are widely employed in solar-thermal applications to attain high temperatures. The purpose of this study is to determine how much entropy is created when Powell-Eyring nanofluid (P-ENF) flows across porous media on a horizontal plane under thermal jump circumstances. The flow in PTSC was generated by nonlinear surface stretching, thermal radiation, and Cattaneo-Christov heat flux, which was utilized to compute heat flux in the thermal boundary layer. Using a similarity transformation approach, partial differential equations were converted into ordinary differential equations with boundary constraints. Then, the boundary restrictions and partial differential equations were merged to form a single set of nonlinear ordinary differential equations. To obtain approximate solutions to ordinary differential equations, the Keller-Box approach is utilized. Nanofluids derived from silver- and copper-based engine oil (EO) has been employed as working fluids. The researchers observed that changing the permeability parameter reduced the Nusselt number while increasing the skin frictional coefficient. Total entropy variation was also calculated using the Brinkman number for flow rates with Reynolds number and viscosity changes. The key result is that thermal efficiency is inversely proportional to particular entropy production. For example, using Cu-EO nanofluid instead of Ag-EO nanofluid increased the heat transport rate efficiency to 15–36%.

Inherent imprecisions present in the basic parameters of cellular honeycomb cores, such as the cell angle, the material properties, and the geometric parameters, need to be considered in the analysis and design to meet the high-performance requirements. In this paper, imprecisions associated with the basic parameters of honeycomb cores are considered. Non-probabilistic models for the in-plane elastic properties of hexagonal honeycomb cores are developed in which the imprecisely defined input and response parameters are represented by only their mean values and variations without the requirement of knowing the probability density distributions of the imprecise parameters as is required for probabilistic methods. Thus, the proposed models predict not only the nominal values of the in-plane elastic properties but also their variations from the respective mean values. The applicability of the proposed models is demonstrated by considering the analysis of the in-plane elastic properties of a honeycomb core made of aluminum 5052-H-32 in which the core material properties are defined by their mean values and variations. The results show that realistic variations of the in-plane elastic properties are obtained using the proposed non-probabilistic models. The sensitivity of the in-plane elastic properties to the imprecisions present in each basic parameter is also investigated.

The basic or primitive parameters of composite laminates, such as the constituent materials properties, the thickness of each ply, the ply orientations and the applied loads, exhibit variabilities, hence, the response of the laminated composites also exhibits some degree of variability. Thus, the accuracy and reliability of the laminates cannot be assured if the variabilities present in the basic parameters are ignored. In the past decades, the probabilistic approach has been used widely to simulate the uncertainties in the macromechanics of composite laminates. However, the exact probability distributions of the primitive parameters are not known in most of the applications. This work, for the first time, models the uncertainties in the macromechanics of composite laminates using the interval analysis and the universal grey system theory by representing the primitive parameters as intervals. Also, for comparison, a probabilistic approach is presented with plus/minus three standard deviations about the mean of the response. Due to the so-called dependency problem, the interval analysis predicts wider and inaccurate ranges. Thus, a truncation-based interval analysis procedure with a suitable truncation parameter is used to overcome the limitation associated with the original interval analysis. Specifically, in this work, the uncertainties in the in-plane and flexural engineering constants and laminae stresses are studied. The environmental effects on the laminae stresses are also investigated. Numerical examples are presented to demonstrate the application of the three interval-based uncertainty methods for the behavior of composite laminates by considering different stacking sequences of graphite/epoxy and glass/epoxy laminates.

In this study, the accuracy of applying artificial neural networks and response surface methodology in estimating kSiO2/EG was examined. Thermal conductivity prediction in the temperature range of 5–65 °C and mass fractions of 0.005–5 wt.% was performed. Considering the constraints of minimizing the mean square error (MSE) as well as maximizing the R-squared value, the most appropriate polynomial based on linear regression (for RSM) and the optimal number of neurons were obtained through performing the least squares methodology. Statistical calculations showed that MSE value for ANN and RSM techniques was 0.0000342 and 0.0001577, respectively. Comparing the R-squared values of ANN (0.993) and RSM (0.968) methods, it was found that from this perspective, the artificial neural network is superior. Comparing the results of the simulation and the laboratory, it was observed that both methods are not very accurate at low mass fractions. However, the potential of the ANN technique was greater than RSM one. Also, the usefulness of SiO2/EG nanofluid through helically coiled tube heat exchanger (HCTHE) was challenged from the perspective of the second law of thermodynamics. Performing exergy balance revealed that the exergy destruction is intensified at higher mass fraction and lower temperature. Applying RSM on irreversibility affirmed that the cubic linear regression led to statistical criteria of $$R^{2} = 0.9999$$ and MOD less than $$0.008\%$$ , and therefore, it is recommended to navigate the exergy destruction through HCTHE.

In the context of the finite elements analysis, the mechanical performance of viscoelastically bonded smart structures is investigated and analyzed. Three different models are considered and compared. In the 1st model, the actuator is glued to the host structure. On the other hand, in the two other models the actuator is glued to the bonding layer which is glued to the host structures. To explore the effect of the bonding layer characteristics on the mechanical behavior of the host structure, both elastic and viscoelastic layers are considered. The Prony’s series are utilized to simulate the viscoelastic constitutive response. The mathematical formulation of the coupled problem is presented and the dynamic finite elements equations of motion of the coupled electromechanical systems are introduced. The proposed methodology is verified by comparing the obtained results with the available results in the literature and good consentience is observed. Both static and dynamic vibration behaviors are studied incorporating the interfacial shear stresses between the bonding layer and the host structure as well as the displacements as a comparison criterion to determine the performance controlling function of the host structure. Parametric study of piezoelectric properties showed that permittivity is required in solving such systems but does not affect the performance. On the other hand, the piezoelectric characteristics have significant effects on the mechanical performance of smart structures and can be used in the optimum selection of combination just like mechanical properties and geometry. Additionally, the obtained results show that the model with viscoelastic bonding layer has an overall static performance nearly half of elastic bonding layer model while it has a slight effect on the dynamic behavior compared with the corresponding elastic bonding layer. The proposed methodology with the obtained results is supportive in the applications of structure health monitoring and dynamics of smart structural systems. The proposed procedure could be extended in a future work to include the coupled electromagnetic effects on the dynamic behavior of smart structures in hygrothermal environment.

In this paper, a new uncertainty-based approach, termed the universal grey number-based Gaussian elimination method, is presented for the analysis of large structures that require the solution of systems of linear interval algebraic equations. Although exact ranges of the solution can be found using the enumeration method, it is known to be computationally expensive as it requires a large number of analyses. Although interval analysis has been used by some researchers, it is found to lead to wider ranges of the response quantities due to the dependency problem. Hence, modified procedures such as the truncation-based interval analysis have been suggested in the literature to overcome the dependency problem. In fact, no interval analysis-based method is available in the literature for solving large number of interval linear equations accurately. The present method is expected to overcome the limitations associated with the available methods in terms of accuracy and computational effort. To demonstrate the accuracy of the proposed method, the stress analysis of several truss structures under specified interval values of input parameters is considered. It is shown that the proposed method yields accurate results more efficiently with less computational effort compared to the truncation-based interval analysis and enumeration method.

Current article aims to numerically scrutinize and compare the forced convection in three different configurations of a 3D heat sink. Two models of porous were designed aiming to evaluate the effects of nanomaterial and metallic foam to the conventional solid heat sink on thermal performance. In these two models, porous material with the same volume fraction was located in two different positions to have different contact areas with the solid. MWCNT-Fe3O4 hybrid nanofluid has been utilized as coolant working fluid. Validations were carried out in the critical case of 47 W for pure water through comparison with previous experimental work in which the whole surface of the CPU is covered with porous media. According to the results, at the constant Reynolds number, the heat sinks, which are consist of metallic foam, have better cooling performance and are able to decrease the surface temperature of heat sink more.

In this study, the thermal behavior of the wall by adding phase change material in the presence of solar radiation was investigated. Phase change material with a melting point of 21–23 °C was added to the wall and then its effect on heat transfer was inspected. By numerically solving the energy equation, the temperature distribution within the wall was obtained and then, using Newton's law of cooling, heat transfer from the inner surface was obtained. The results showed that if a thickness of 1 cm is added to the western, eastern, southern and northern walls, it will affect heat transfer and reduce it by 18.5, 18.1, 17.4 and 17%, respectively. Hence, the effect of Phase change material on heat transfer of the main walls is not much different. Then, the effect of thickness was explored and it was found that for a building that is equipped with at thickness 1 cm, heat transfer reduced by 3.69 k W h m 2 . J u l y . This figure at 2, 3, 4 and 5 cm was 4.07, 4.39, 4.69 and 4.96 k W h m 2 . J u l y .

Extensive work has been done in the past few decades to quantify the uncertainties associated with the micromechanics of composite materials in the presence of uncertainties in constituent material properties using probabilistic approaches. However, the probabilistic approaches require a knowledge of the probability distributions of the input parameters which are not known in most cases. This work presents interval-based uncertainty analysis using probabilistic approach with three sigma band about the mean, interval analysis method and the universal grey system (number) theory. Since the interval analysis predicts wider ranges and, in some cases, might violate the physical laws of the problem, the truncation-based interval analysis is presented to overcome the overestimation caused in the computed quantities by the so-called dependency problem associated with the interval analysis. The uncertainties exhibited in the micromechanics characteristics of composite materials due to the presence of uncertainties in the constituent material properties are investigated. The propagation of these uncertainties to the response characteristics of an angle-ply lamina is also studied. In the numerical study, two types of composite materials are considered – the graphite/epoxy and glass/epoxy systems – to demonstrate and compare the influence of the uncertainty models on the results. This work shows that improved and more meaningful results can be obtained using the universal grey system theory compared to the interval analysis, truncation-based interval analysis and probabilistic method for the micromechanics of composite materials and the response of an angle-ply lamina when the fiber and matrix properties are uncertain.

Graphene is simply one atomic layer of graphite, which can be synthesized from Flake Graphite, through Top-Down method. It has applications in thermal and energy systems such as Solar collector. A Flat-plate Solar collector collects the sunlight and transfers the heat energy to the tubes. The used fluid can be Nanofluid. In this study, first, Graphene/Silica-Water nanofluid prepared at varied mass fractions (0.1 to 0.4 wt%). Then, thermal conductivity and viscosity (for 12.23 and 122.3 S-1 shear rates) were measured at varied temperatures (25 to 50 °C). In order to reduce the cost of experiments, Artificial Neural Network algorithms (Levenberg Marquardt and Orthogonal Distance Regression) and Fuzzy model were trained and compared to find the trend of heat transfer and Viscosity. Also, Graphene/Silica-Water nanofluid was employed as Flat-plate Solar collector fluid to enhance the efficiency. Again, Artificial Neural Network algorithms and Fuzzy model were trained and compared to find the best model for trend prediction. This research presents novel equations for trend prediction of G/SiO2-Water Nanofluid for enhancing the efficiency of industrial thermal and energy systems. Further, results displayed better trend prediction of Fuzzy model versus LM/ODR training ANN algorithms.

The idea behind Flat-plate Solar collector is uncomplicated, Sun heats a flat surface, that collect as much energy as desirable, and then the energy is shifted to water, or alternate fluid for additional purpose. Titanium Dioxide has employed in electric conductors and electrical ceramics, while Silicon Dioxide has employed in semiconductors. In this research, Titanium Dioxide and Silicon Dioxide were mixed to make a composite. XRD and FESEM tests were studied to confirm the phase, and then, the composite dispersed in water to make a nanofluid. Thermal conductivity of the nanofluid (at 1.0 to 4.0 wt%) was measured via hot-transient technique (at 25 to 50 °C). Then, ANN algorithms and Fuzzy models employed to find the investigation-trend. Moreover, nanofluid used in Flat-plate Solar-collector and its efficiency enhancement was measured. Then, ANN algorithms and Fuzzy models employed to find the investigation-trend. Results indicated the trend of thermal conductivity and efficiency enhancement of TiO2/SiO2 nanofluid, and proved its high capability in energy systems.

To scrutinize the role of variable Lorenz force on treatment of ferrofluid within a complex preamble zone, numerical simulation has been done in this study. Existence of external magnetic source creates variable Lorentz force and enclosure with two sinusoidal walls was made from porous media. Mixture of iron oxide and H2O with concentration of 0.04 leads to considering homogeneous model for operating fluid. Adding the new source terms in equations creates complex model and CVFEM was utilized to solve the equations in form of vorticity. Impact of porous zone was incorporated according to non-Darcy model. Verification test proves low deviation with previous published article. Impacts of Lorentz and buoyancy terms as well as permeability on behavior of fluid were examined in view of contours and bar charts. As magnetic force employs, speed of nanoparticles declines and distortion of isotherms reduces. Lower temperature of hot wall obtains with augment of permeability and Ra. Higher permeability of zone makes higher velocity of nanofluid. Augment of Ha for highest value of Ra leads to reduction of strength of eddy about 11.76%. Temperature of inner surface decreases about 4.7% with augmentign Da. Growing Ra and Da makes Nu to augment by 131.29% and 2.66%. Also, increase of Ha leads to decline of Nu about 2.82%. Involving nanoparticles and radiation effect makes the Nu to enhance about 89.76% and 7.17%.

This paper presents the energy consumption analysis of the refrigerator and the effect of the condenser on it. According to the Bureau of Energy Efficiency (BEE), India, the energy efficiency of electric appliances is the key parameter for testing their performance before domestic use. For energy consumption analyses, the experimentation was conducted on the domestic refrigerator (165 L) top-mounted evaporator by retrofitting the refrigerator with an Elliptical Helical Coil Condenser (EHCC) and existing refrigerator with a Straight Tube Condenser (STC). Box-Behnken Design (BBD) is very significant in determining the significant factor and reducing the number of experiments. BBD has been performed to analyze the significance of factors ambient temperature, fresh food compartment temperature and the heat load in energy consumption, and the Coefficient of Performance (COP) of a refrigerator. The heat load and the ambient temperature are both very significant in determining the refrigerator's energy consumption. The most important thing is to increase the liquid content in the charge before it is supplied to the evaporator to extract more amount of heat to increase the cooling effect. The ANOVA (Analysis of Variance) results show that the ambient temperature and the heat load were more significant in increasing energy consumption and decreasing the COP and vice versa. The results of ANOVA and the experiment are very close; the R2 value 0.995 precisely matches the R2 adj. value 0.994. The statistical analysis using the Box-Behnken design produces a good fitting of the modeled and experimental data set. The present study aims to examine the effects of said factors and the condenser on the domestic refrigerator's energy consumption and COP. The study exhibits some enhancement in the COP to 2.59 contrary to 2.45 and energy consumption reduced to 1191 Wh from 1755 Wh during the trial of 24 h.

Nanofluids have better surface stability, thermal absorption, and distribution capacities are produced as heat transfer fluids. In current nanofluid-transport studies, together with the heat transfer mechanisms, entropy reduction in thermo- and non-Newtonian nanofluid models with changing thermophysical characteristics is heavily addressed. The entropy production is examined as thermodynamically stable first-grade viscoelastic nanofluid (FGVNF) flow over a flat penetrable, porous barrier. The uniform porous horizontal stretching of the surface in a Darcy type of pore media results in a fluid motion disturbance. In addition, this study also includes the effects of thermal radiation, viscous dissipation, and slip conditions at the border. Under boundary layer flow and Rosseland approximations, the governing mathematical equations defining the physical features of the FGVNF flow and heat transfer models are summarized. The governing nonlinear partial differential equation is transformed by similarity variables to achieve solutions in nonlinear ordinary differential equations. Approximative solutions for reduced ordinary differential equations are obtained by the Keller Box Scheme. Two distinct types of nanofluids, Copper-Engine Oil (Cu-EO) and Zirconium Dioxide-Engine Oil (ZrO2-EO), are considered in this research. The graphs are produced to examine the effects of the different physical factors for the speed, temperature, and entropy distributions. The significant findings of this study are that the critical characteristics of (boundary layer) BL collectively promote temperature variation, including slip speed, diverse thermal conductivity, and non-Newtonian first-grade viscoelastic nanofluid, the concentration of nanoparticles as well as thermal radiation, and a high porous media. The other noteworthy observation of this study demonstrates that the (Cu-EO) FGVNF is a better conductor than (ZrO2-EO) FGVNF transmission. The entropy of the system grows the Deborah number and volume fraction parameter.

Molecular Dynamic (MD) approach is used to describe the temperature and pressure effects on the Al nanoparticles aggregation process in the aqueous environment of water as the base liquid. For this goal, various physical parameters like total energy, temperature, aggregation time, and total energy of the simulated structures, are reported. The results show that the aggregation process enlarges by the ratio of temperature and pressure. By atomic mobility increasing, the Al nanoparticles collide with each other in a shorter simulation time. Numerically, by temperature increases from 300 K to 350 K, the aggregation time decreases from 1.33 ns to 1.18 ns. Furthermore, aggregation time increases to 1.99 ns by more pressure to 5 bar.

In the Saudi Arabia climate zone, the share of cooling in buildings sector energy usage is 66%. In this study, the main goal is to reduce energy usage in the cooling sector, which was investigated with the introduction of phase change material (PCM) and recovery unit (RU). By incorporation of the enthalpy-porosity technique into the energy equation, the thermal behavior of the PCM-based walls along with the ceiling was modeled transiently throughout the year. Taking into account high solar intensity in Saudi Arabia region, the sol-air temperature was defined to consider the effects of solar irradiance on the building envelopes. To meet the cooling requirements in the building, an air handling unit (AHU) combined with an absorption chiller was used. The annual calculations affirmed that by adding PureTemp (melting temperature of 22-24°C) the heat gain decreased by 7.13% which in turn led to an energy-saving by 47.3 k W h m 2 . Moreover, due to the incorporation of a RU into AHU, the energy demand in AHU was lowered by 63.8 k W h m 2 (equivalent to an 8.38% reduction). Finally, by using the energy-efficient techniques of adding PCM and installing RU, the AHU energy usage was decreased by 14.6% which was equivalent to a 111.1 k W h m 2 . y e a r energy-saving

Taking into account a share of 42.4% of total energy usage for buildings, utilizing of energy reduction techniques in this sector will be effective. In this article, transient energetic analysis along with the exergetic study of an air handling unit (AHU) equipped with a heat recovery unit (HRU) were examined. The transient analysis was performed in July by developing a program based on the energy/exergy balance equations. The results showed that owing to using the phase change material (PCM), heat exchange diminished by 545 kWh July (8.6% reduction). Owing to using of a heat recovery unit, the cooling load energy demand lowered by 4043 kWh July (10% reduction). Although the irreversibility through the cooling experienced a 20% reduction due to the addition of an HRU, but the total irreversibility decreased by only 0.4%. Integrating the solar system with AHU + HRU led to energy-saving by 1832 kWh (11.6% reduction). Moreover, the total irreversibility reduced by 9% due to using the solar system. Finally, it was found that the solar system accounts for 83.62% of the total irreversibility.

Vacancy defect influence on the physical manner of Ar-Al nanofluid inside a nanochannel is described. All Molecular Dynamics (MD) simulations are performed by using Large Scale Atomic/Molecular Massively Parallel Simulator (LAMMPS). The Universal Force Field together with Embedded Atom Model, UFF & EAM, are examined to simulate the nanofluid composed of Al nanoparticles dispersed in Al as the base fluid, streaming inside the Al nanochannel. Physical parameters such as potential energy, density, velocity, and temperature profiles are calculated for nanofluids' atomic structure. These calculations show that the vacancy defect would cause to decrease the density, and increase the velocity and temperature to 0.089 atom/A3, 0.036 A/ps, and 560 K. So it can be said that vacancy defect implementing might change the atomic manner of mixture and also can manipulate the nanofluid performance in the heat and mass transfer applications.