Transmission lines are generally subjected to faults, so it is advantageous to determine these faults as quickly as possible. This study uses an Artificial Neural Network technique to locate a fault as soon as it happens on the Doukan-Erbil of 132kv double Transmission lines network. CYME 7.1-Programming/Simulink utilized simulation to model the suggested network. A multilayer perceptron feed-forward artificial neural network with a back propagation learning algorithm is used for the intelligence locator's training, testing, assessment, and validation. Voltages and currents were applied as inputs during the neural network's training. The pre-fault and post-fault values determined the scaled values. The neural network's performance was evaluated, and tests were run. Line-to-ground faults were examined. The study demonstrates how effective, rapid, and precise this method is at locating faults. The neural network's performance was examined, and tests were run on it. The overall performance of the mean square error in the trained network execution was 0.11792 at 35 epochs. The correlation coefficient at the entire target was 0.99987 percent of an error on the Doukan-Erbil double transmission lines.
The calculation of the oil density is more complex due to a wide range of pressuresand temperatures, which are always determined by specific conditions, pressure andtemperature. Therefore, the calculations that depend on oil components are moreaccurate and easier in finding such kind of requirements. The analyses of twenty liveoil samples are utilized. The three parameters Peng Robinson equation of state istuned to get match between measured and calculated oil viscosity. The Lohrenz-Bray-Clark (LBC) viscosity calculation technique is adopted to calculate the viscosity of oilfrom the given composition, pressure and temperature for 20 samples. The tunedequation of state is used to generate oil viscosity values for a range of temperatu
... Show MoreThe present study develops an artificial neural network (ANN) to model an analysis and a simulation of the correlation between the average corrosion rate carbon steel and the effective parameter Reynolds number (Re), water concentration (Wc) % temperature (T o) with constant of PH 7 . The water, produced fom oil in Kirkuk oil field in Iraq from well no. k184-Depth2200ft., has been used as a corrosive media and specimen area (400 mm2) for the materials that were used as low carbon steel pipe. The pipes are supplied by Doura Refinery . The used flow system is all made of Q.V.F glass, and the circulation of the two –phase (liquid – liquid ) is affected using a Q.V.F pump .The input parameters of the model consists of Reynolds number , w
... Show MoreThe majority of the environmental outputs from gas refineries are oily wastewater. This research reveals a novel combination of response surface methodology and artificial neural network to optimize and model oil content concentration in the oily wastewater. Response surface methodology based on central composite design shows a highly significant linear model with P value <0.0001 and determination coefficient R2 equal to 0.747, R adjusted was 0.706, and R predicted 0.643. In addition from analysis of variance flow highly effective parameters from other and optimization results verification revealed minimum oily content with 8.5 ± 0.7 ppm when initial oil content 991 ppm, tempe
Nowadays power systems are huge networks that consist of electrical energy sources, static and lumped load components, connected over long distances by A.C. transmission lines. Voltage improvement is an important aspect of the power system. If the issue is not dealt with properly, may lead to voltage collapse. In this paper, HVDC links/bipolar connections were inserted in a power system in order to improve the voltage profile. The load flow was simulated by Electrical Transient Analyzer Program (ETAP.16) program in which Newton- Raphson method is used. The load flow simulation studies show a significant enhancement of the power system performance after applying HVDC links on Kurdistan power systems. Th
... Show More<p>Analyzing X-rays and computed tomography-scan (CT scan) images using a convolutional neural network (CNN) method is a very interesting subject, especially after coronavirus disease 2019 (COVID-19) pandemic. In this paper, a study is made on 423 patients’ CT scan images from Al-Kadhimiya (Madenat Al Emammain Al Kadhmain) hospital in Baghdad, Iraq, to diagnose if they have COVID or not using CNN. The total data being tested has 15000 CT-scan images chosen in a specific way to give a correct diagnosis. The activation function used in this research is the wavelet function, which differs from CNN activation functions. The convolutional wavelet neural network (CWNN) model proposed in this paper is compared with regular convol
... Show MoreThis paper presents a study of a syndrome coding scheme for different binary linear error correcting codes that refer to the code families such as BCH, BKLC, Golay, and Hamming. The study is implemented on Wyner’s wiretap channel model when the main channel is error-free and the eavesdropper channel is a binary symmetric channel with crossover error probability (0 < Pe ≤ 0.5) to show the security performance of error correcting codes while used in the single-staged syndrome coding scheme in terms of equivocation rate. Generally, these codes are not designed for secure information transmission, and they have low equivocation rates when they are used in the syndrome coding scheme. Therefore, to improve the transmiss
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