The electrical and thermal performance of a typical single pass hybrid photovoltaic/thermal (PV/T) air collector is modeled, simulated and analyzed for two selected case studies in Iraq. An improved mathematical thermo-electrical model is derived in terms of design, operating and climatic parameters of the hybrid solar collector to evaluate its important characteristics: collector flow and heat removal factors, PV maximum power point and its temperature coefficient, and overall power and efficiency. Unlike previous PV/T thermal models, the present model is obtained with some additions and corrections in radiation and convection heat coefficients for the top loss and for the air duct with more applicable sky temperature correlation. The well-known 5-parameter electrical model of PV module is solved using improved boundary conditions and translation equations for better convergence and accuracy. The voltage temperature coefficient of the PV module is included in the boundary conditions for convergence stability. The module parameters are taken to be dependent on solar radiation and PV cell temperature for improved accuracy. A Matlab computer simulation program is developed to solve the thermo-electrical model. The developed model is verified with previously published experimental results and theoretical simulations; it is proved to be most accurate in respect to percentage errors and correlation coefficients. Different parameters of the PV/T collector such as cell and air temperatures, thermal gain, PV current and voltage, and fill factor have been investigated. The results identified the effects of most important operating conditions such as sky, inlet and cell temperatures, air flow rate and incident solar radiation on the performance of the hybrid collector. The approved model is applied for a winter day (22 January 2011) in Baghdad city and for a summer day (20 May 2011) in Fallujah city. It is found that the electrical, thermal and overall collector efficiencies for the two case studies were 12.3%, 19.4% and 53.6% respectively for the winter day, while that for the summer day were 9%, 22.8% and 47.8%.
Coronavirus disease (COVID-19) is an acute disease that affects the respiratory system which initially appeared in Wuhan, China. In Feb 2019 the sickness began to spread swiftly throughout the entire planet, causing significant health, social, and economic problems. Time series is an important statistical method used to study and analyze a particular phenomenon, identify its pattern and factors, and use it to predict future values. The main focus of the research is to shed light on the study of SARIMA, NARNN, and hybrid models, expecting that the series comprises both linear and non-linear compounds, and that the ARIMA model can deal with the linear component and the NARNN model can deal with the non-linear component. The models
... Show MoreThe investigation of the effect of tempering on thermal analysis of
Al-Ti-Si alloy and its composites with MgO and SiC particles was
performed. Thermal analysis was performed before and after
tempering by DSC scan. Optical microscopy was used to identify the
phases and precipitations that may be formed in base alloy and
composites. X-ray diffraction test indicated that the Al3Ti is the main
phase in Al-Ti-Si alloy in addition to form Al5Ti7Si12 phase. Some
chemical reactions can be occurred between reinforcements and
matrix such as MgO.Al2O3 in Al-Ti/MgO, and Al4C3 and Al(OH)3 in
Al-Ti/SiC composite. X-ray florescence technique is used to
investigate the chemical composition of the fabricated specimens.
H
In this work, the performance of the receiver in a quantum cryptography system based on BB84 protocol is scaled by calculating the Quantum Bit Error Rate (QBER) of the receiver. To apply this performance test, an optical setup was arranged and a circuit was designed and implemented to calculate the QBER. This electronic circuit is used to calculate the number of counts per second generated by the avalanche photodiodes set in the receiver. The calculated counts per second are used to calculate the QBER for the receiver that gives an indication for the performance of the receiver. Minimum QBER, 6%, was obtained with avalanche photodiode excess voltage equals to 2V and laser diode power of 3.16 nW at avalanche photodiode temperature of -10
... Show MoreTitanium dioxide nanotube arrays (TiO2 NTAs) were successfully decorated with nanoclusters of cobalt by an electrochemical deposition method. This Co-TiO2 NTAs nanostructure exhibited high compatibility with aluminum chloride\ chloroacetamide (an ionic liquid) and calcium chloride dihydrate\ acetamide (a deep eutectic solvent), leading to significant improvements in the electrochemical properties of the system. Significantly, this led to a discernible augmentation in both potential and current values, concomitant with a decrease in internal resistance. The presence of cobalt facilitated a faster transfer of electric charge, enhancing the overall efficiency of the system. Moreover, the incorporation of cobalt exhibited a ben
... Show MoreUltra-High Temperature Materials (UHTMs) are at the base of entire aerospace industry; these high stable materials at temperatures exceeding 1600 °C are used to manage the heat shielding to protect vehicles and probes during the hypersonic flight through reentry trajectory against aerodynamic heating and reducing plasma surface interaction. Those materials are also recognized as Thermal Protection System Materials (TPSMs). The structural materials used during the high-temperature oxidizing environment are mainly limited to SiC, oxide ceramics, and composites. In addition to that, silicon-based ceramic has a maximum-use at 1700 °C approximately; as it is an active oxidation process o
A new azo dye, 5,5-[1,2-phenylenebis(2,1-biazenediyl)]bis[8-quinolino], was synthesized by reacting the diazonium salt of o-phenylenediamine with 8-hydroxyquinoline. The ligand was subsequently used to prepare a series of metal complexes with V(IV), Fe(III), Cr(III), Mn(II), Mo(VI), and Ru(III). The ligand was characterized using 1H and 3C-NMR spectroscopy, while the metal complexes were analyzed using UV-Vis, FT-IR, and mass spectrometry, along with thermal analysis (TGA, DSC), (C.H.N.), conductivity measurements, magnetic susceptibility, and metal and chlorine content analysis, the results indicated that the ligand exhibits tetracoordination. The complexes predominantly formed octahedral geometries, except for the vanadium complex, which
... Show MoreA cost-effective and efficient detector was created to conduct thorough turbidimetric measurements by reaction of Co (II) ion with calcium ferro cyanide to form bright green particulate, using the method of continuous flow injection analysis, the use of NAG-5SX1-1D-SSP Analyzer in determining cobalt (II) ion in a test for the validity of the new design. The NAG-5SX1-1D-SSP Analyzer is composed of five irradiation sources of white snow leds having the diameter of 10 mm with one solar cell of 55 mm length, 13.5 mm width. Using a selector switch to select the optimum voltage to be used which was 2.7 VDC. Under conditions of optimization, cobalt (II) ion was determined at 0.005–20 mmol. L–1(n = 23) while linearity dynamic range 0.005–7 mm
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
... Show MoreImage classification is the process of finding common features in images from various classes and applying them to categorize and label them. The main problem of the image classification process is the abundance of images, the high complexity of the data, and the shortage of labeled data, presenting the key obstacles in image classification. The cornerstone of image classification is evaluating the convolutional features retrieved from deep learning models and training them with machine learning classifiers. This study proposes a new approach of “hybrid learning” by combining deep learning with machine learning for image classification based on convolutional feature extraction using the VGG-16 deep learning model and seven class
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