The inhibitive action of a blend of sodium nitrite/sodium hexametaphosphate (SN+SHMP) on corrosion of carbon steel in simulated cooling water systems (CWS) has been investigated by weight loss and electrochemical polarization technique. The effect of temperature, velocity, and salts concentrations on corrosion of carbon steel were studied in the absence and presence of mixed inhibiting blend. Also the effect of inhibitors blend concentrations (SN+SHMP), temperatures, and rotational velocity, i.e., Reynolds number (Re) on corrosion rate of carbon steel were investigated using Second-order Rotatable Design (Box-Wilson Design) in performing weight loss and corrosion potential approach. Electrochemical polarization measurements were used to study the behavior of carbon steel in different salts concentrations of (CWS) with pH = 7.5 in absence and presence of the inhibiting blend. The results show that the regression model (Box-Wilson Design) that has been developed using experimental data was used to verify that the interaction term of temperature with inhibitors blend and the square term of inhibitors blend are significant for corrosion rate in 0.05 N NaCl solution while the main variables are not pronounced. Also, it is found that the corrosion rate of carbon steel is increased with increasing temperature, rotational velocity, and NaCl salts concentration in uninhibited and inhibited solutions. Inhibition performance of NaNO2+ Na(PO3)6 was found to increase with its concentration up to 800 ppm inhibitors blend, and the corrosion potential is shifted to more positive direction with increasing rotational velocity, and inhibitor blend concentration.
This investigation was carried out to study the treatment and recycling of wastewater in the Battery industry for an effluent containing lead ion. The reuse of such effluent can only be made possible by appropriate treatment method such as electro coagulation.
The electrochemical process, which uses a cell comprised aluminum electrode as anode and stainless steel electrode as cathode was applied to simulated wastewater containing lead ion in concentration 30 – 120 mg/l, at different operational conditions such as current density 0.4-1.2 mA/cm2, pH 6 -10 , and time 10 - 180 minute.
The results showed that the best operating conditions for complete lead removal (100%) at maximum concentration 120 mg/l was found to be 1.2 mA/cm2 cur
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This study aims to identify the amount of the effect of the ability to learn the individuals within the organization on the accumulation of intellectual capital and the role it plays in improving the performance of the organization, and to achieve that, the researcher designed a questionnaire to collect data and information from the surveyed respondents and analyzed using SPSS software, the study concluded after testing hypotheses to have a direct impact between the capacity for organizational learning and the accumulation of intellectual capital, which in turn affects the accumulation of intellectual capital as a positive and direct impact on the performance of the organization, al
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Survival analysis is widely applied in data describing for the life time of item until the occurrence of an event of interest such as death or another event of understudy . The purpose of this paper is to use the dynamic approach in the deep learning neural network method, where in this method a dynamic neural network that suits the nature of discrete survival data and time varying effect. This neural network is based on the Levenberg-Marquardt (L-M) algorithm in training, and the method is called Proposed Dynamic Artificial Neural Network (PDANN). Then a comparison was made with another method that depends entirely on the Bayes methodology is called Maximum A Posterior (MAP) method. This method was carried out using numerical algorithms re
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This paper aims to decide the best parameter estimation methods for the parameters of the Gumbel type-I distribution under the type-II censorship scheme. For this purpose, classical and Bayesian parameter estimation procedures are considered. The maximum likelihood estimators are used for the classical parameter estimation procedure. The asymptotic distributions of these estimators are also derived. It is not possible to obtain explicit solutions of Bayesian estimators. Therefore, Markov Chain Monte Carlo, and Lindley techniques are taken into account to estimate the unknown parameters. In Bayesian analysis, it is very important to determine an appropriate combination of a prior distribution and a loss function. Therefore, two different
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In this study, we used Bayesian method to estimate scale parameter for the normal distribution. By considering three different prior distributions such as the square root inverted gamma (SRIG) distribution and the non-informative prior distribution and the natural conjugate family of priors. The Bayesian estimation based on squared error loss function, and compared it with the classical estimation methods to estimate the scale parameter for the normal distribution, such as the maximum likelihood estimation and th
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In this research, the efficiency of low-cost unmodified wool fibers were used to remove zinc ion from industrial wastewater. Removal of zinc ion was achieved at 99.52% by using simple wool column. The experiment was carried out under varying conditions of (2h) contact time, metal ion concentration (50mg/l), wool fibers quantity to treated water (70g/l), pH(7) & acid concentration (0.05M). The aim of this method is to use a high sensitive, available & cheep natural material which applied successfully for industrial wastewater& synthetic water, where zinc ion concentration was reduced from (14.6mg/l) to (0.07mg/l) & consequently the hazardous effect of contamination was minimized.
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