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Motorized shades have a considerable impact on energy demand reduction of building, combining it with lighting systems and PV panels will make it more effective. In this article, three shade design, two lighting control system (on/off, dimming) and the option of using PV cells in shades have been investigated. The best combination of above cases which maximizes annual electrical energy saving and minimizes return on investment’s time is found. Annual saving is calculated using hourly simulation of lighting, solar heat flux and electricity generation. Results showed that the optimum combination have the saving potential of 792kwh annually.

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This study covers the exergy analysis of the condensate stabilization unit of South Pars Gas Refinery. In this regard, the simulation of unit is carried out using HYSYS software to achieve all required data for exergy calculations. The final product is suitable for summer, as the Reid Vapor Pressure is achieved about 7 Psia. Afterwards, the exergy analysis is done using source-sink or stream-wise methods. Having analyzed all unit operations, it is shown that condensate tower and the associated heat exchanger have the most scope for energy improvement.

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In this study, the performance of a solar greenhouse heating system equipped with a linear parabolic concentrator and a dual-purpose flat plate solar collector‏ was investigated using the Artificial Neural Network (ANN) method. The heat required for the greenhouse at night hours was supplied by the heat stored in the storage tank by the solar system during the sunshine time and  an auxiliary heater. A water pump was used to make a forced-flow through the concentrator assembly. While, a natural water flow occurred in the flat plate collector. ANN method was used to predict  the tank temperature and energy consumption from the heat storage tank and by the auxiliary heater. Network inputs were solar radiation intensity, ambient temperature, wind speed, collector surface temperature, greenhouse temperature, flow rate and time. About 80% of total data were used for training, 10% for testing and 10% for validation. The results indicated that the network topology of 7-15-1 with R² and MSE of respectively 0.98 and 0.00017 presented the best results for prediction of energy consumption from the tank. While the most suitable description for variations of energy consumption by the auxiliary heater and from storage tank was given by the network topologies‏ of 7-10-10-1 (with R² of 0.99 and MSE of 0.00014) and 7-5-15-1 (with R² 0.98 of MSE  of 0.00011), respectively.

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The application of personalized ventilation systems, particularly in the buildings, is one of the new topics that today presented to it, because of their proper performance in reducing energy consumption and creating better thermal comfort conditions. In the current study, the energy consumption of a personalized cooling system installed in a room, considering the constraint of thermal comfort, was evaluated and compared with a non-personalized cooling system. The dimensions of the room equal to 4×3×2.7 m³ and includes a return air outlet (for both personalized and non-personalized situations), a supply air inlet in a non-personalized situation, two air inlets for personalized ventilation, table, chair and an approximate model of a human. OpenFOAM numerical solver was used for the calculation and solving the governing equations. Results indicate that in the status of the use of the personalized cooling system, Predicted Mean Vote (PMV) changes in the presence of the person is much higher than the status of the use of the non-personalized cooling system. The local thermal discomfort parameter stemming from draught is within allowed range (less than %20) for a personalized cooling system, excluding of in velocity of 2 m/s and temperature of 21.1 °C. The other important result is that the energy consumption of the personalized cooling system reported much less than the non-personalized cooling system so that energy saving was achieved in about 50 percent. In personalized cooling mode, desired conditions of thermal comfort and minimum energy consumption obtained only at the velocity of 1 m/s and temperature of 20.5 °C among the cases investigated

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In recent years, the use of modeling methods that directly utilize empirical data is increasing due to the high accuracy in predicting the results of the process, rather than statistical methods. In this paper, the ability of Artificial Neural Network (ANN) and Adaptive Fuzzy-Neural Inference System (ANFIS) models in the prediction of the thermal performance of Al₂O₃ nanofluid that is measured by thermal resistance is investigated. The laboratory data was extracted from a valid paper that examined the thermal performance of Al2O3 nanoparticles in an oscillating tube. For modeling by ANN, a multi-layered perceptron network was used and for ANFIS a sugeno fuzzy model was used that are both the most accurate and most commonly used modeling methods. Comparison of target values ​​with predicted values ​​by both models was highly satisfactory, and the correlation coefficient for both of them was more than 0.99, which indicates that the accuracy of these two models is high. Finally, the performance of both models was compared with each other, which was very good and close, but in general ANN showed better performance than ANFIS.

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The high power coefficient of the Darrius vertical axis wind turbine lift regime has prompted researchers to concentrate their efforts on this regime, despite the fact that these turbines suffer from major problems in the drag-lift regime. In the present study, in addition to exploring the performance of the Darrius type wind turbine at blade tip speeds above 1, the effect of design factors on its performance at TSRs below 1 is also investigated. The results were extracted from numerical analysis recruiting Fluent software and the k-w SST turbulence model. The effect of blade type, thickness, and chord length on turbine performance has been investigated. The blade angle at TSR less than one was calculated using a new equation, and the results were evaluated. The numerical simulation results showed that increasing the chord length for symmetric and asymmetric airfoils from 0.1 to 0.2 m enhances the turbine performance in drag-lift regime, whereas decreasing chord length improves turbine performance at higher TSRs. The blade with a curvature of 4% and a chord length of 0.1 m has the best performance at TSR 2.25. Increasing the thickness exerts a negative influence on the turbine's performance in both regimes, and at lower TSRs, NACA0018 airfoil with a chord length of 0.2 m was of the optimum performance in the drag-lift regime.