In this study, successive electrocoagulation (EC) and electro-oxidation (EO) processes were used to minimize some of the major pollutants in real wastewater, such as organics (detected by chemical oxygen demand (COD)), and turbidity. The wastewater utilized in the present study was collected from the Midland Refinery Company in Baghdad-Iraq. The performance of the successive batch EC-EO processes was studied by utilizing Graphite and Aluminum (Al) as monopolar anode electrodes and stainless steel (st.st.) as the cathode. The Taguchi experimental design approach was used to attain the best experimental conditions for COD reduction as a major response. Starting from chemical oxygen demand COD of (600 ppm), the effects of current density (C.D.) (10- 20 mA/cm2), pH (4- 10), time (2– 4 h), and NaCl concentration (1.5- 2.5 g/l) on the efficiency of COD reduction were examined. The results indicated that COD reduction increased with increasing C.D., NaCl conc., and electrolysis time and increased exponentially at pH (4). The best conditions for the treatment of this wastewater were: C.D. (20 mA/cm2), pH (4), time (4 h), and NaCl conc. (2.5 g/l). At these conditions, approximately 98.12 % of COD reduction was achieved with electrical energy consumption (ENC) of about 62.04 kWh/m3. The result of analysis of variance (ANOVA) revealed that the C.D. and pH have a higher influence on the performance of organics removal, while the time and NaCl conc. have a minor impact on COD Re%.
In this paper, estimation of system reliability of the multi-components in stress-strength model R(s,k) is considered, when the stress and strength are independent random variables and follows the Exponentiated Weibull Distribution (EWD) with known first shape parameter θ and, the second shape parameter α is unknown using different estimation methods. Comparisons among the proposed estimators through Monte Carlo simulation technique were made depend on mean squared error (MSE) criteria
The comparison of double informative priors which are assumed for the reliability function of Pareto type I distribution. To estimate the reliability function of Pareto type I distribution by using Bayes estimation, will be used two different kind of information in the Bayes estimation; two different priors have been selected for the parameter of Pareto type I distribution . Assuming distribution of three double prior’s chi- gamma squared distribution, gamma - erlang distribution, and erlang- exponential distribution as double priors. The results of the derivaties of these estimators under the squared error loss function with two different double priors. Using the simulation technique, to compare the performance for
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