امیربابک انصاری

Using latent heat storage systems with phase change materials (PCM) is an effective way to store thermal energy, which has been of great interest recently. Using fins is one of the simplest and cheapest ways to increase heat transfer in PCMs and increase the performance of the storage system. Since the fin arrangement has a significant impact on the charging time of the PCM, the main goal of this study is to optimize the fin arrangement in the PCM chamber in a double-pipe heat exchanger in order to decrease the charging time, and thus increase the efficiency of the storage system. For this purpose, the governing equations including conservation of mass, momentum, and energy in a finned double-pipe heat exchanger have been solved using ANSYS-Fluent software to investigate the dynamic behavior of PCM. The thermal-hydraulic performance of PCM at different configurations has been fully analyzed by drawing liquid fraction contours, velocity vectors and streamlines. Also, to find the optimal fin arrangement and maximize the storage performance, the response surface method based on the central composite design have been implemented. The results obtained from the response surface with the reduced cubic equaltion show that compared to the case without fins, the charging time reduces by about 19% using the uniform fin configuration, while reduces about 56% using the optimal fins arrangement, which is a significant amount.

The analysis of heat transfer in the channel in many types of heat exchangers, such as electric cooling equipment, solar collectors, heat exchanger systems, high-performance boilers, gas turbine blade coolers, etc., is the basis of the design, construction, and optimization. Controlling heat transfer to increase the rate of heat transfer in such systems by improving the cooling method is an effective energy engineering from the point of saving energy. Increasing the heat transfer performance in the scales of macro and microchannels is crucial. The use of expanded surfaces in the channel is a practical method to increase the heat transfer coefficient. In the upcoming article, the smart design of a two-dimensional nanofluid heat exchanger has been studied numerically in order to achieve optimal performance conditions in terms of heat transfer rate, the amount of deposition of nanoparticles in the structure of the exchanger, as well as the fluid pressure drop while passing through it. It can be seen that the geometric structure optimized by the combination of genetic algorithm and computational fluid dynamics of this channel causes an increase of 1.14% in the enthalpy of the passing nanofluid, a decrease of 11.21% in the pressure drop of the passing nanofluid, and a reduction of 8.44% percentage in the deposition of nanoparticles inside the channel and a total increase of 24.82% in the fitting function defined in terms of these three variables, compared to the channel designed in previous studies. Therefore, this optimal channel has a higher heat transfer rate with a pressure drop and a lower amount of nanoparticle deposition compared to the previous channel, which proves the ability of the genetic algorithm with computational fluid dynamics in the optimal design of all types of heat exchangers.

This paper present a gas turbine cycle combined with a solid oxide fuel cell with hydrogen fuel’s is exergy and energy modeled. In this way all components of the system are separately modeled. Fuel cell model presented, as well as show its behavior in different condition performance. Then, the effects of various parameters on efficiency, exergy was evaluated. And for accuracy, the results were compared with results of references and shows a good match. Increasing the turbine inlet temperature results in decreasing the thermal and exergy efficiency of hybrid system, whereas it improves the net power output. Moreover, an increase in the turbine inlet temperature leads to increases irreversibility and compression ratio leads to decreases irreversibility of the hybrid system. The results in the design point showed that 81% of irreversibility takes place in the fuel cell and combustion chamber(41% in the SOFC and 40% in combustion chamber). Hybrid system efficiency is 58.4%, while the system without SOFC efficiency is 31%, that is a combination of superior performance system.

Modeling and simulation are useful tools to optimize and analyze the dynamic behavior of lead-acid batteries. One of the main problems is that the governing equations of lead-acid batteries are highly coupled which significantly increases the computational time of numerical methods in simulations. Using reduced order models (ROM) is one of the best ways to overcome this difficulty. In the present study, the one-dimensional electrochemical governing equations of lead-acid battery are solved using model order reduction based on proper orthogonal decomposition (POD). To show the capability of this method, the governing equations including conservation of charge in solid and liquid phases and conservation of species are solved simultaneously for a lead-acid cell during discharge, rest and charge process. The results of reduced order model including cell voltage, acid concentration and state of charge (SoC) are compared to the results of finite-volume method (FVM). The obtained numerical results show that not only the POD-based ROM of lead-acid battery significantly decreases the computational time (speed-up factor of 15) but also there is an excellent agreement with the results of previous computational fluid dynamic (CFD) models.