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.
The primary components of successful engineering projects are time, cost, and quality. The use of the ring footing ensures the presence of these elements. This investigation aims to find the optimum number of geogrid reinforcement layers under ring footing subjected to inclined loading. For this purpose, experimental models were used. The parameters were studied to find the optimum geogrid layers number, including the optimum geogrid layers spacing and the optimum geogrid layers number. The optimum geogrid layers spacing value is 0.5B. And as the load inclination angle increased, the tilting and the tilting improvement percent for the load inclination angles (5°,10°,15°) are (40%,28%, and 5%) respectively. The reduction percent of the
... Show MoreThe primary components of successful engineering projects are time, cost, and quality. The use of the ring footing ensures the presence of these elements. This investigation aims to find the optimum number of geogrid reinforcement layers under ring footing subjected to inclined loading. For this purpose, experimental models were used. The parameters were studied to find the optimum geogrid layers number, including the optimum geogrid layers spacing and the optimum geogrid layers number. The optimum geogrid layers spacing value is 0.5B. And as the load inclination angle increased, the tilting and the tilting improvement percent for the load inclination angles (5°,10°,15°) are (40%,28%, and 5%) respectively. The reduction percent o
... Show MoreThe aim of this study was to investigate the effectiveness of binary solvent for regeneration of spent lubricating oil by extraction-flocculation process. The regeneration was investigated by bench scale experiments by using locally provided solvents (Heavy Naphtha, n-Butanol, and iso-Butanol). Solvents to used oil, mixing time, mixing speed and temperatures were studied as operating parameters. The performance on three estimated depended key parameters, namely the percentage of base oil recovered (Yield), percent of oil loss (POL), and the percent of sludge removal (PSR) were used to evaluate the efficiency of the employed binary solvent on extraction process. The best solvent to solvent ratio for binary system were 30:70 for Heavy Naph
... Show MoreThe Journal of Studies and Researches of Sport Education (JSRSE)
Generally, statistical methods are used in various fields of science, especially in the research field, in which Statistical analysis is carried out by adopting several techniques, according to the nature of the study and its objectives. One of these techniques is building statistical models, which is done through regression models. This technique is considered one of the most important statistical methods for studying the relationship between a dependent variable, also called (the response variable) and the other variables, called covariate variables. This research describes the estimation of the partial linear regression model, as well as the estimation of the “missing at random” values (MAR). Regarding the
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