This paper presents a novel experimental work for cooling photovoltaic panels using water saturated zeolite/activated alumina. Different system configurations, with 4 different zeolite thicknesses, were tested indoor. Moreover, the zeolite was tested with different added components (fins and metal mesh/particles) for enhancing the system performance. Three different radiations intensities were set for a period of 6 hours and the results were compared with the uncooled system. The experimental results showed a significant solar panels temperature reduction of approximately 14.9°C and 9 °C for radiation intensities of 600 and 1000 W/m 2 respectively. The expected electrical efficiency, according to this temperature reduction, was calculated and an average enhancement of 10% and 7% at radiation of 600 and 1000 W/m 2 intensity respectively was estimated.

This paper aims to present a new and novel experimental study for the usage of hydrogel beads with different bed configurations as a cooling attachment underneath solar panel. Four different bed configurations were studied using different layers and fins arrangements then compared with the un-cooled system. The best results were obtained using 3 rows of hydrogel beads with fins where the panel temperature dropped by approximately 10 ̊ C below the uncooled panel at 1000 W/m 2 (representing around 14% temperature drop comparing to the panels' initial temperature) leading to an increase in the electricity generation efficiency of 7.2 % compared with the un-cooled system.

No abstract

Auger-based transportation systems are a promising method to transport lunar regolith for in situ resource utilisation. An analytical model based on terrestrial auger conveyor industry guidelines is used to predict the behaviour and performance parameters of an auger conveyor system under a range of initial conditions. Key aspects of the model have been validated with published experimental data. The proposed model produces more accurate predictions than previous methods and calculates the inclination angle with the best conveying efficiency. The proposed model output flow predictions have on average $$47\%$$ 47 % less deviation from the experimental data mean than previous model predictions, while the predictions for power requirements without considering energy losses present 42.9% and $$59.2\%$$ 59.2 % less deviation than previous predictions. When the losses are considered, the proposed model predictions are 70% and $$86.4\%$$ 86.4 % more accurate than the previous models, which have been found to underestimate the power requirements of this type of conveyors.