In this work, corrosion parameters were evaluated using potentiodynamic polarization curves. In order to determine corrosion parameters of potential and current density of the interesting metal, carbon steel, environmental conditions of external corrosion of buried carbon steel pipeline in Iraqi soil were prepared in the laboratory using simulated prepared conditions. Solutions of sodium chloride at different concentrations (300, 1100, 1900, 2700, and 3500 ppm) were used. pH of solution were acidic at pH =5, and alkaline at pH = 9. Laboratory conditions were similar to those of Iraqi soil where the pipelines were buried. Temperature was constant at 20 °C. Potentiodynamic polarization curves, of potential vs. log current density, were obtained using M Lab Multi-Channel Potentiostat/Galvanostat. The carbon steel coupon (ASTM A179-84A) was used as the studied metal. The results of this work reveal the behavior of carbon steel in external corrosion conditions under Iraqi soil. The rate of corrosion, of carbon steel, increases with the increase in chloride concentration in solution. As pH changes from acidic to alkaline medium, the rate of corrosion decreases.
Abstract—The upper limb amputation exerts a significant burden on the amputee, limiting their ability to perform everyday activities, and degrading their quality of life. Amputee patients’ quality of life can be improved if they have natural control over their prosthetic hands. Among the biological signals, most commonly used to predict upper limb motor intentions, surface electromyography (sEMG), and axial acceleration sensor signals are essential components of shoulder-level upper limb prosthetic hand control systems. In this work, a pattern recognition system is proposed to create a plan for categorizing high-level upper limb prostheses in seven various types of shoulder girdle motions. Thus, combining seven feature groups, w
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A new simple and sensitive spectrophotometric method for the determination of trace amount of Co(II) in the ethanol absolute solution have been developed. The method is based on the reaction of Co(II) with ethyl cyano(2-methyl carboxylate phenyl azo acetate) (ECA) in acid medium of hydrochloric acid (0.1 M) givining maximum absorbance at ((λmax = 656 nm). Beer's law is obeyed over the concentration range (5-60) (μg / ml) with molar absorptivity of (1.5263 × 103 L mol-1 cm-1) and correlation coefficient (0.9995). The precision (RSD% ˂ 1%). The stoichiometry of complex was confirmed by Job's method which indicated the ratio of metal to reagent is (2:1). The studied effect of interference elements Zn(II), Cu(II), Na(I), K(I), Ca(II) and Mg
... Show MoreThe proper operation, and control of wastewater treatment plants, is receiving an increasing attention, because of the rising concern about environmental issues. In this research a mathematical model was developed to predict biochemical oxygen demand in the waste water discharged from Abu-Ghraib diary factory in Baghdad using Artificial Neural Network (ANN).In this study the best selection of the input data were selected from the recorded parameters of the wastewater from the factory. The ANN model developed was built up with the following parameters: Chemical oxygen demand, Dissolved oxygen, pH, Total dissolved solids, Total suspended solids, Sulphate, Phosphate, Chloride and Influent flow rate. The results indicated that the constructed A
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The investigation of determining solutions for the Diophantine equation over the Gaussian integer ring for the specific case of is discussed. The discussion includes various preliminary results later used to build the resolvent theory of the Diophantine equation studied. Our findings show the existence of infinitely many solutions. Since the analytical method used here is based on simple algebraic properties, it can be easily generalized to study the behavior and the conditions for the existence of solutions to other Diophantine equations, allowing a deeper understanding, even when no general solution is known.
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Many consumers of electric power have excesses in their electric power consumptions that exceed the permissible limit by the electrical power distribution stations, and then we proposed a validation approach that works intelligently by applying machine learning (ML) technology to teach electrical consumers how to properly consume without wasting energy expended. The validation approach is one of a large combination of intelligent processes related to energy consumption which is called the efficient energy consumption management (EECM) approaches, and it connected with the internet of things (IoT) technology to be linked to Google Firebase Cloud where a utility center used to check whether the consumption of the efficient energy is s
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