Globally, buildings use about 40% of energy. Many elements, such as the physical properties of the structure, the efficiency of the cooling and heating systems, the activity of the occupants, and the building’s sustainability, affect the energy consumption of a building. It is really difficult to predict how much energy a building will need. To improve the building’s sustainability and create sustainable energy sources to reduce carbon dioxide emissions from fossil fuel combustion, estimating the building's energy use is necessary. This paper explains the energy consumed in the lecture building of the Al-Khwarizmi College of Engineering, University of Baghdad (UOB), Baghdad, Iraq. The weather data and the building construction information were collected for a specific period and put into a specific data set. That data was used to find the value of energy consumption in the building using artificial intelligence and data analysis. A Python library called Scikit-learn is used to implement machine learning algorithms. In particular, the Multi-layer Perceptron regressor (MLPRegressor) algorithm was used to predict the consumption. The importance of this work lies in predicting the amount of energy consumed. The outcomes of this work can be used to predict the energy consumed by any building before it is built. The used methodology shows the ability to predict energy performance in educational buildings using previous results and train the model on them, and prediction accuracy depends on the amount of data available for the training in artificial intelligence (AI) steps to give the highest accuracy. The prediction was checked using root-mean-square error (RMSE) and coefficient of determination (R²) and we arrived at 0.16 and 0.97 for RMSE and R², respectively.
Artificial roughness applied to a Solar Air Heater (SAH) absorber plate is a popular technique for increasing its total thermal efficiency (ηt−th). In this paper, the influence of geometrical parameters of V-down ribs attached below the corrugated absorbing plate of a SAH on the ηt−th was examined. The impacts of key roughness parameters, including relative pitch p/e (6–12), relative height e/D (0.019–0.043), angles of attack α (30–75°), and Re (1000–20,000), were examined under real weather conditions. The SAH ηt−th roughened by V-down ribs was predicted using an in-house developed conjugate heat-transfer numerical model. The maximum SAH ηt−th was shown to be 78.8% as predicted under the steady-state condition
... Show More
(3)
(2)
(4)
(3)
Solar collectors, in general, are utilized to convert the solar energy into heat energy, where it is employed to generate electricity. The non-concentrating solar collector with a circular shape was adopted in the present study. Ambient air is heated under a translucent roof where buoyant air is drawn from outside periphery towards the collector center (tower base). The present study is aimed to predict and visualize the thermal-hydrodynamic behavior for airflow under inclined roof of the solar air collector, SAC. Three-dimensional of the SAC model using the re-normalization group, RNG, k−ε turbulence viscus model is simulated. The simulation was carried out by using ANSYS-FLUENT 14.5. The simulation
... Show More
(1)
The solar photocatalytic degradation of diuron, which is one of the herbicides, has been studied by a solar pilot plant in heterogeneous solar photocatalysis with titanium dioxide. The pilot plant was made up of compound parabolic collectors specially designed for solar photocatalytic applications. The influence of different variables such as, H2O2 initial concentration, TiO2 initial concentration, and diuron initial concentration with their relationship to the degradation efficiency were studied. Hydrogen peroxide (H2O2) found to increase the rate of diuron degradation. The best removal efficiency of heterogeneous solar photocatalytic TiO2 system was found to be 46.65 % and for heterogeneous solar photocatalytic TiO2/ H2O2 system was fo
... Show More
(3)
(2)
In this paper, an experimental study of the thermal performance for hybrid solar air conditioning system was carried out, to investigate system suitability for the hot climate in Iraq. The system consists of vapor compression unit combined with evacuated tube solar collector and liquid storage tank. A three-way valve was installed after the compressor to control the direction flow of the refrigerant, either to the storage tank or directly to the condenser. The performance parameters were collected by data logger to display and record in the computer by using LabVIEW software. The results show that the average coefficient of performance of hybrid solar air conditioning system (R=1) was about 2.42 to 2.77 and the average p
... Show More
(2)
An experimental study was conducted to determine the performance of a solar electric refrigeration system. The system contained flat photovoltaic solar panel which absorbs the solar energy and convert it to electrical energy, used to run the refrigeration cycle. Two refrigeration cycles with electrical solar panel were used over a period of 12 months, the first one with classical parts known in refrigeration cycle, while the second one introduced heat exchanger which improves the coefficient of performance by saving the consumed energy. The coefficient of performance of these refrigeration cycles with compressor efficiency 85% are 2.102 and 2.57 respectively. The overall efficiency of the two systems are 18.9% and 23.13%.
High-resolution imaging of celestial bodies, especially the sun, is essential for understanding dynamic phenomena and surface details. However, the Earth's atmospheric turbulence distorts the incoming light wavefront, which poses a challenge for accurate solar imaging. Solar granulation, the formation of granules and intergranular lanes on the sun's surface, is important for studying solar activity. This paper investigates the impact of atmospheric turbulence-induced wavefront distortions on solar granule imaging and evaluates, both visually and statistically, the effectiveness of Zonal Adaptive Optics (AO) systems in correcting these distortions. Utilizing cellular automata for granulation modelling and Zonal AO correction methods,
... Show More
Copper with different concentrations doped with zinc oxide nanoparticles were prepared from a mixture of zinc acetate and copper acetate with sodium hydroxide in aqueous solution. The structure of the prepared samples was done by X-ray diffraction, atomic force microscopy (AFM) and UV-VIS absorption spectrophotometer. Debye-Scherer formula was used to calculate the size of the prepared samples. The band gap of the nanoparticle ZnO was determined by using UV-VIS optical spectroscopy.
(14)
(4)