The energy and exergy performance of a parabolic dish collector is investigated experimentally and theoretically. The e ect of receiver type, inlet temperature and mass ow rate of heat transfer uid (HTF), receiver temperature, receiver aspect ratio and solar radiation are investigated. To evaluate the e ect of the receiver aperture area on the system performance, three aperture diameters are considered. It is deduced that the fully opened receivers have the greatest exergy and thermal e ciency. The cylindrical receiver has greater energy and exergy e ciency than the conical one due to less exergy destruction. It is found that the highest exergy destruction is due to heat transfer between the sun and the receivers and counts for 35 % to 60 % of the total wasted exergy. For three selected receiver aperture diameters, the exergy e ciency is minimum for a speci ed HTF mass ow rate. High solar radiation allows the system to work at higher HTF inlet temperatures. To use this system in applications that need high temperatures, in cylindrical and conical receivers, the HTF mass ow rates lower than 0.05 and 0.09 kg/s are suggested, respectively. For applications that need higher amounts of energy content, higher HTF mass ow rates than the above mentioned values are recommended.

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Abstract This work seeks to explore the permeability dependence of polyurethane (PU)/polyethylene glycol (PEG) blend membranes on the molecular weight and composition of PEG constituent polymer. In this regard, gases with different polar nature were mixed (CO2/N2, CO2/CH4, and O2/N2) and subjected to a series of PU/PEG blends prepared via solution casting method. With the alteration of the molecular weight (1000, 2000, and 6000 g/mol) and composition (0, 10, 15, and 20 wt.%) of PEG in the blend films, the potentials of membranes in controlling the permeation of gas molecules within the films were quantified, compared, and discussed. It is known that the introduction of PEG into PU-based membranes causes the films to become more flexible, which brings advantages from an application point of view. Fourier transform infrared spectroscopy, wide-angle X-ray diffraction, and scanning electron microscopy analyses were used to study the microstructural changes in the prepared PU/PEG blend membranes. The selectivity of the films was obviously displaced by the introduction of PEG, particularly when higher-molecular-weight PEGs were used and the resulting hybrid membranes were subjected to a mixture of CO2/CH4 or CO2/N2 gases.

In this study, the solar photocatalytic process in a pilot plant with compound parabolic collectors (CPCs) was performed for amoxicillin (AMX) degradation, an antibiotic widely used in the world. The response surface methodology (RSM) based on Box-Behnken statistical experiment design was used to optimize independent variables, namely TiO dosage, antibiotic initial concentration, and initial pH. The results showed that AMX degradation efficiency affected by positive or negative effect of variables and their interactions. The TiO dosage, pH, and interaction between AMX initial concentration and TiO dosage exhibited a synergistic effect, while the linear and quadratic term of AMX initial concentration and pH showed antagonistic effect in the process response. Response surface and contour plots were used to perform process optimization. The optimum conditions found in this regard were TiO dosage = 1.5 g/L, AMX initial concentration = 17 mg/L, and pH = 9.5 for AMX degradation under 240 min solar irradiation. The photocatalytic degradation of AMX after 34.95 kJ/L accumulated UV energy per liter of solution was 84.12 % at the solar plant.

An artificial neural network (ANN) approach was used to obtain a simulation model to predict the rotating disc contactor (RDC) performance during the extraction of aromatic hydrocarbons from lube oil cuts, to produce a lubricating base oil using furfural as solvent. The field data used for training the ANN model was obtained from a lubricating oil production company. The input parameters of the ANN model were the volumetric flow rates of feed and solvent, the temperatures of feed and solvent, and the disc rotation rate. The output parameters were the volumetric flow rate of the raffinate phase and the extraction yield. In this study, a feed-forward multi-layer perceptron neural network was successfully used to demonstrate the complex relationship between the mentioned input and output parameters.