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EN
Photovoltaic (PV) power prediction is vital for efficient and effective solar energy utilization within the energy ecosystem. It enables grid stability, cost savings, and the seamless integration of solar power into the broader energy infrastructure. In this work, previously obtained data on the estimation of the power produced by a PV, which is cooled by L-shaped aluminum fins attached to the backside of the PV at different spacings, is used to predict the power produced by the PV. This is achieved by employing both neural network models and multiple linear regression (MLR) techniques to assess the correlation between power generated by PV with L-shaped aluminum fins and its input variables. Two distinct approaches were employed for this purpose. The first approach involved the conventional MLR model, while the second utilized a neural network, specifically the multilayer perceptron (MLP) model. The estimated outcomes were subsequently compared against the previously measured data. The MLP model showed a great ability to identify the relationship between input and output variables, it was noted. The statistical error study provided evidence of data mining’s acceptable accuracy when using the MLP model. Conversely, the results indicated that the MLR technique exhibited the least ability to estimate the power generated by PV with L-shaped aluminum fins.
EN
One way to cut down the consumption of diesel fuel in domestic heating in Jordan is to blend it with shale oil, which may be extracted from oil shale. This leads to a cut down in the national fuel bill in Jordan. Unfortunately, shale oil contains significant amounts of sulfur as impurities and upon burning sulfur oxides are emitted causing a negative environmental impact, and hence desulfurization of such fuel blends is essential. This may be achieved by adding activated carbon to the fluids. The process of removing sulfur from shale oil is crucial for safeguarding the environment, human well-being, and equipment, as well as meeting regulatory requirements and creating superior-quality goods. In this study, a domestic boiler was utilized to evaluate the degree of desulfurization process of blends of diesel and shale oil fuels upon their burning in a domestic boiler, to achieve this, blends of both fuels were prepared with varying amounts of shale oil (10%, 20%, 30%, and 40%) and various amounts of activated carbon were added to the prepared mixtures of diesel fuel and shale oil. The assessment of performance included examining the environmental impact, specifically by analyzing exhaust gases to measure the concentration of Sulfur Oxide (SO2). It was found that an increase in the concentration of shale oil in the mixture led to an increase in the concentration of SO2. However, adding more activated carbon to the mixture from the fuels resulted in a decrease in the SO2 concentration. The lowest SO2 concentration was observed when 1g of activated carbon was added per liter of the fuel mixture at a 20% concentration of shale oil, and 0.6g of activated carbon per liter of the fuel mixture at a 40% concentration of oil shale.
EN
Multiple linear regression and artificial neural network (ANN) models were utilized in this study to assess the type influence of nanomaterials on polluted water disinfection. This was accomplished by estimating E. coli (E.C) and the total coliform (TC) concentrations in contaminated water while nanoparticles were added at various concentrations as input variables, together with water temperature, PH, and turbidity. To achieve this objective, two approaches were implemented: data mining with two types of artificial neural networks (MLP and RBF), and multiple linear regression models (MLR). The simulation was conducted using SPSS software. Data mining was revealed after the estimated findings were checked against the measured data. It was found that MLP was the most promising model in the prediction of the TC and E.C concentration, s followed by the RBF and MLR models, respectively.
EN
Solar water disinfection (SODIS) is a simple and low-cost method of increasing water quality. However, it takes about 6 hours of exposure to solar radiation. The elimination of harmful pathogenic germs from drinking water can be accelerated using a combination of sun disinfection and nanotechnology. In this study, a hybrid water purification technique using solar water disinfection, Titanium Oxide (TiO2), and natural mineral clays was investigated. TiO2, natural kaolin clay nanoparticles, and a mixture of TiO2 and natural clay were added to contaminated wastewater containers at different concentrations. After that, the containers were exposed to sun light for different time intervals. Samples were then collected from all tests to measure the total counts of Total Coliform and Escherichia coli (E. coli) using the IDEXX system. The results showed that the addition of TiO2 and natural kaolin clay to wastewater with solar water disinfection reduced the total count of the pathogenic microorganisms and decreased the time needed time for the disinfection process compared to using solar energy alone. The results also showed that the optimum concentration of the TiO2, which yielded the shortest purification time and lowest levels of pathogenic microorganisms, was 0.006 g/ml. In co ntrast, the most effective concentratio n of natural clay was 0.0015 g/ml. Moreover, the results showed that the optimum concentration of the mixture of TiO2 and natural clay, which speeds up the purification time an d lowest the level of pathogen ic microorganisms was 0.006 g/ml for TiO2 and 1.2 g/ml for the natural clay.
EN
Due to emergency situations, many people are living under degraded conditions as displaced persons and refugees. Unfortunately, shelters commonly used in humanitarian context do not ensure comfortable conditions for their occupants. This study investigates the impact of utilizing passive climatization techniques on the indoor thermal comfort of the occupants in refugee settlements under Jordan’s climate using the Design Builder software. Several passive techniques were simulated, including orientation, floor, wall and roof insulation, and natural ventilation. The simulation results indicated that the thermal comfort has improved when using the aforementioned techniques by 9.72% offering 23% comfort hours throughout the year.
EN
Unlike conventional fresh water producing systems, from saline or brackish water, the innovative solar water producing systems are efficient and effective. Experiments were conducted on two identical roof-type solar stills and simultaneously tested under the same weather conditions. One of these stills was modified by integrating a vacuum pump to lower the pressure inside while the other still was used as a reference unit. Different concentrations of Al2O3 nanoparticles were chosen, 0.2%, 0.4%, and 0.6%, and used with water inside the modified still. It was verified that the modified still, without nanoparticles, yields 34.84% more production than the conventional still. In addition, the modified still with a 0.4% of Al2O3 nanoparticles produced the highest percentage of distilled water, 44.42% in comparison to the one without the use of Al2O3 nanoparticles, followed by 37.94% and 24.07% for 0.6% and 0.2% of Al2O3 nanoparticles, respectively.
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