This study aims to optimize the economic thermodynamics of a flat plate solar collector and investigate transient heat transfer. This study focuses on modeling and optimization under unfavorable radiation conditions. The method employed here is optimization using a multi-objective genetic algorithm with the assistance of MATLAB software. The key components include objective functions, constraints, and design variables, which are the collector efficiency and the annual total price. The results indicate that increasing the length of the collector has a negative impact on the thermodynamic efficiency and increases the total annual price. Conversely, increasing the width of the collector initially improves the thermodynamic efficiency but then decreases it while also increasing the total annual price. Furthermore, increasing the number of pipes leads to a decrease in the total annual price and an initial increase followed by a decrease in the thermodynamic efficiency. The research was conducted over four different days.

Today, the use of alternative fuels that have plant origin has attracted the attention of most countries because these fuels emit less pollution. In this research, bioethanol production has been evaluated considering solar energy sources. In the present study, the possibility of developing net-zero energy concepts in a bioethanol production plant as one of the most consumed energy industries in the field of bio-systems of the country from a technical and economic perspective was investigated. The purpose of this research is to model the bioethanol production plant with the aim of achieving zero net energy using a photovoltaic system. In addition, technical and economic analyzes have been used in different approaches for a more detailed investigation. According to the modeling done, in the Zero net energy approach, the results showed that the maximum production of electrical energy by the photovoltaic cell is 76.6 GWh/yr. For this approach, the return on investment is 10.7 years. The area required to install photovoltaic modules in this approach is very large and equal to 88,334 m².

In this article, new multiple-production systems based on the micro-combined cooling, heating and power (CCHP) cycle with biomass heat sources are presented. In this proposed system, absorption refrigeration cycle subsystems and a water softener system have been used to increase the efficiency of the basic cycle and reduce waste. Comprehensive thermodynamic modeling was carried out on the proposed system. The validation of subsystems and the optimization of the system via the genetic algorithm method was carried out using Engineering Equation Solver (EES) software. The results show that among the components of the system, the dehumidifier has the highest exergy destruction. The effect of the parameters of evaporator temperature 1, ammonia concentration, absorber temperature, heater temperature difference, generator 1 pressure and heat source temperature on the performance of the system was determined. Based on the parametric study, as the temperature of evaporator 1 increases, the energy efficiency of the system increases. The maximum values of the energy efficiency and exergy of the whole system in the range of heat source temperatures between 740 and 750 K are equal to 74.2% and 47.7%. The energy and exergy efficiencies of the system in the basic mode are equal to 70.68% and 44.32%, respectively, and in the optimization mode with the MOOD mode, they are 87.91 and 49.3, respectively.

This study aims at sport buildings and discussing mathematical models' applications focused on energy problems, both on the thermal and electrical sides. Methanol is a type of alcohol that can be used as an alternative fuel option. Solid oxide fuel cells are a type of fuel cell that have advantages over other types of fuel cells such as high efficiency and low emissions. Researchers are exploring the use of methanol in solid oxide fuel cells, because it can be converted into synthetic gas at certain temperatures using catalysts. This study focuses on a system that uses solar energy for combined cooling, cooling, heating, and power generation. Solar energy is a renewable and environmentally friendly source of energy. Methanol is synthesized and then converted into gases for use in solid oxide fuel cells. This process is called reforming. A fuel cell and a gas turbine system can increase power generation and provide heat for cooling with a conversion efficiency exceeding 64%, but 15% of energy is lost due to light and heat losses.

One of the most important applications of composites is their use in structures with periodic thermal loading. Sports buildings are one of the most appropriate options for using these composites due to the need for a balanced temperature. In this research, composite samples of polymeric base reinforced with nanoparticles, structure, and effects of thermal cycling and circular holes on it have been investigated. The nanoparticles used were multi-walled carbon nanotubes and the weight percentage was 0.1%. In this research, the behavior of perforated nanocomposite samples with a diameter of 2 and 4 mm holes under thermal cycles was investigated. By performing a tensile test on the samples, the fracture toughness and modulus of elasticity due to the number of different heating cycles and the ratio of the hole diameter to the width for different samples were checked and compared. According to the results, as the ratio of diameter to width increases, the coefficient of stress concentration also increases. Also, the results show that the fracture strength increases during the thermal cycle. Fracture strength increases between 9% and 25% after 360 thermal cycles. It seems that one reason for this increase in tensile strength is the sintering of glass/epoxy nanocomposite during the thermal cycle.

Today, the use of wind energy by wind turbines has grown significantly, and this development is due to the production of required energy and tourism attraction of wind turbines. But according to the standard technologies used in this industry, the operating costs are very high. For this reason, before the construction of wind farms, potential measurements should be done along with economic analysis. Therefore, in this research, a statistical analysis of wind farms has been done. In the statistical analysis, Weibull and Rayleigh distribution functions were used to predict the wind speed of the studied area. MATLAB software is used to model prediction functions. Among the important results of wind speed prediction by the Weibull distribution function, it can be mentioned that the wind speed is variable between 0.6 and 7 m/s in the studied area. The total power density and wind energy in the 10 years are equivalent to 28 W/m2 and 810/0534 kWh/m2 at the height of 10 m calculated.