The Response Surface Method as an Experimental Design Technique to Explore and Model the Performance of Corrosion Inhibitors

Abstract

Numerous environmental factors strongly affect performance of inhibitors performance. Therefore many experimental tests and much time are needed to fully explore the inhibitor performance in various conditions. This paper deals with introducing response surface method (RSM) using central composite face-centered design as a method in order to explore and mathematically model the inhibitors behavior in different working conditions. Also, this method provides us the ability of significantly decreasing the number of experiments. In this study, as an example, the effect of temperature, hydrochloric acid and inhibitor concentrations on inhibitive behavior of 4-aminophenyl disulphide for mild steel is examined. Further, two mathematical models are established to estimate mild steel corrosion rate in the inhibited and uninhibited solutions. Analysis of variance (ANOVA) is applied to check the adequacy of models. Finally, the Langmuir adsorption energy is calculated using the acquired models. The results show that despite the inhibitor efficiency changes in various conditions, the adsorption type onto metal is an invariable parameter.

Corrosion resistance of hot-dip galvanized steel in simulated soil solution: A factorial design and pit chemistry study

“…respectively. The 3D graphs are presented to evaluate the relationship between the independent variables and the response [48]. The 3D plots show that both temperature and citric acid concentration have a significant effect on i corr and the maximum i corr is expected when temperature and citric acid concentration are at high levels.…”

Inhibition of Bicarbonate-Chloride Corrosion and Passivation of Carbon Steel under Open-Circuit Conditions by Molybdate

“…40 However, it has not been widely used in corrosion research with only a few groups using this technique and its variants such as Response Surface Methodology. [41][42][43] DOE is useful in screening out input parameters that have insignificant effects and also determining whether there are interaction effects between the input parameters, e.g. whether the presence of factor X 1 affects the effect of factor X 2 on the output Y.…”