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Due to the great potential of ionic liquid (ILs) for solar energy storage, this work combines computer-aided ionic liquid design (CAILD) and a TRNSYS simulation to identify promising IL candidates as simultaneous thermal storage media and heat transfer fluids. First, a mixed-integer nonlinear programming (MINLP) problem is formulated to search for optimal IL structures, where the thermal storage density integrating the IL density, heat capacity, melting point, and desorption temperature is employed as the objective function and the physical properties, i.e. thermal conductivity and viscosity, are implemented as optimization constraints. After that, TRNSYS simulations of a solar energy power system with the designed ILs as thermal fluids are conducted during a typical meteorological year to further study the practical performance of the IL candidates. Through the analyses of annual system operation performance as well as the long-term cost savings of such a system, the application feasibility and sustainability of the designed ILs for solar energy storage are well interpreted.

2018 Elsevier Ltd The heat transfer properties of phase change materials (PCMs) are of importance for the efficiency assessment on the heat storage and release in solar thermal systems. Previous research results demonstrate that the increase of thermal conductivity of PCMs can enhance the thermal performance in solar thermal systems; however, the corresponding mechanism is not clear. To this end, this work investigates the influence of PCMs properties on storage performance of solar thermal systems. First, experimental testing was conducted to verify the effectiveness of a thermal simulation model in the heat storage and release process. Then, the proposed simulation model was used to investigate the performance of several commonly used PCMs in the process of melting and solidification. The influence of thermal conductivity and phase transition temperature on the thermal storage properties was analyzed. The analysis results demonstrated that the influence of phase transition temperature on the thermal system performance was greater than that of the thermal conductivity in short time, while the thermal conductivity contributed greater influence on the system performance in long time. The phase transition temperature hardly affected the total system efficiency if given enough heat transfer time. The findings in this work may provide a theoretical reference for the selection of heat storage materials.

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The raising process has been widely used in manufacturing fabric productions. After raising the surface of the fabric, productions are covered with a fluff layer. The quality of the fabric surface is often valuated by the fluffing type. In order to objectively assess the fluff quality of the fabric surface, an optimal sensing method is proposed in this paper. The fluff contour image was firstly collected by the light-cut imaging device. Then, the fluff region was segmented by the adaptive image segmentation method, the contour coordinates of the fabric were extracted using the freeman chain code and constructed in the form of the binary image. Lastly, a back-propagation neural network (BPNN) was used to learn the relationship between the contour coordinates and the fluff quality. On this basis, a practical fabric fluff detection platform was developed based on the optimal sensing technique. Experimental tests were conducted to evaluate the performance of the proposed method in detecting the fluff quality with four different colours and different fluffing processes. Furthermore, the actual fabric inspection was carried out. The detection correct rate can reach 94.17 %, which can meet the practical production requirement.

With the increasing of global energy requirements and environmental problems, the use of solar thermal energy has attracted widespread attention. The selective solar absorption coating is the most important part of a solar thermal conversion device. At present, most of the coatings work well in a vacuum at a high temperature, while not stably in the air environment. Based on the high-temperature resistant and infrared-reflective properties of ITO, a multilayer film of SiO2/Si3N4/SiO2/ITO/Cr has been designed as a selective solar absorber. The genetic algorithm is applied to optimize the material and thickness selection for each layer. The results show that the optimized multilayer film could achieve a high solar absorptance up to 90% while keeping a relatively low infrared emittance around 50% for temperature change between 600°C and 900°C. All the materials composing this film have been tested before to be chemically stable at a high temperature up to 900°C in the air environment. It is also adaptive to different incident angles from 0° to 60°. The finite-difference time-domain method was also adopted to plot the energy density distribution for different wavelengths, which provided the underlying mechanism for the selective emission spectrum. The findings in this study would provide valuable guidance to design a low-cost selective solar absorption coating without the need for vacuum generation.

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