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Thermosyphons have high effective thermal conductivity and are applicable for different heat transfer purposes including cooling devices and heat exchangers. In the present study, thermal performance of a thermosyphon is experimentally investigated by using Ni/Glycerol-water nanofluid in three concentrations including 0.416, 0.625 and 1.25 g/lit. Experimental results revealed that using the nanofluid with 0.625 g/lit concentration leads to lowest thermal resistances. Afterwards, a thermosyphon-based heat exchanger is designed and numerically investigated to compare its performance with copper heat exchanger. Since the effective thermal conductivity of thermosyphon depends on temperature difference between condenser and evaporator, a novel approach is applied to achieve precise modeling. Effects of mass flow rates of cold and streams and inlet temperature of hot stream on heat transfer rate are evaluated. Results revealed that using thermosyphon instead of copper tubes with the same dimensions results in more than 100% improvement in heat transfer capacity. Moreover, it is concluded that increase in the mass flow rates of the streams and inlet temperature of hot stream lead to increase in heat transfer rate. A 3D graph is represented to evaluate the influences of hot stream temperature and mass flow rate on the heat transfer rate of thermosyphon-based heat exchanger.

Summary It is believed that fossil fuel sources are exhaustible and also the major cause of greenhouse gas emission. Therefore, it is required to increase the portion of renewable energy sources in supplying the primary energy of the world. In this study, it is focused on application of nanotechnology in exploitation of renewable energy sources and the related technologies such as hydrogen production, solar cell, geothermal, and biofuel. Here, nanotechnologies influence on providing an alternative energy sources, which are environmentally benign, are comprehensively discussed and reviewed. Based on the literature, employing nanotechnology enhances the heat transfer rate in photovoltaic/thermal (PV/T) systems and modifies PV structures, which can improve its performance, making fuel cells much cost‐effective and improving the performance of biofuel industry through utilization of nanocatalysts, manufacturing materials with high durability and lower weight for wind energy industry.

Nanofluid viscosity is an important physical property in convective heat transfer phenomena. However, the current theoretical models for nanofluid viscosity prediction are only applicable across a limited range. In this study, 1277 experimental data points of distinct nanofluid relative viscosity (NF-RV) were gathered from a plenary literature review. In order to create a general model, adaptive network-based fuzzy inference system (ANFIS) code was expanded based on the independent variables of temperature, nanoparticle diameter, nanofluid density, volumetric fraction, and viscosity of the base fluid. A statistical analysis of the data for training and testing (with R 2 = .99997) demonstrates the accuracy of the model. In addition, the results obtained from ANFIS are compared to similar experimental data and show absolute and maximum average relative deviations of about 0.42 and 6.45%, respectively. Comparisons with other theoretical models from previous research is used to verify the model and prove the prediction capabilities of ANFIS. Consequently, this tool can be of huge value in helping chemists and mechanical and chemical engineers -especially those who are dealing with heat transfer applications by nanofluids -by providing highly accurate predictions of NF-RVs.

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BackgroundAnomalous use of antibiotics and their entrance into the environment have increased concerns around the world. These compounds enter the environment through an incomplete metabolism and a considerable amount of them cannot be removed using conventional wastewater treatment. Therefore, the main objectives of this research are evaluation of the feasibility of using ultraviolet radiation (UV-A) and fortified nanoparticles of titanium dioxide (TiO2) doped with Fe+3 to remove penicillin G (PENG) from aqueous phase and determining the optimum conditions for maximum removal efficiency.ResultsThe results showed that the maximum removal rate of penicillin G occurred in acidic pH (pH = 3) in the presence of 90 mg/L Fe+3-TiO2 catalyst. In addition, an increase in pH caused a decrease in penicillin G removal rate. As the initial concentration of penicillin G increased, the removal rate of antibiotic decreased. Moreover, due to the effect of UV on catalyst activation in Fe+3-TiO2/UV-A process, a significant increase was observed in the rate of antibiotic removal. All of the variables in the process had a statistically significant effect (p < 0.001).ConclusionThe findings demonstrated that the antibiotic removal rate increased by decreasing pH and increasing the amount of catalyst and contact time. In conclusion, Fe+3-TiO2/UV-A process is an appropriate method for reducing penicillin G in polluted water resources.