Abstract
Previously, many empirical models have been used to predict corrosion rates under
different CO2 corrosion parameters conditions. Most of these models did not predict
the corrosion rate exactly, besides it determined effects of variables by holding some
variables constant and changing the values of other variables to obtain the regression
model. As a result the experiments will be large and cost too much. In this paper
response surface methodology (RSM) was proposed to optimize the experiments and
reduce the experimental running. The experiments studied effects of temperature (40
– 60 °C), pH (3-5), acetic acid (HAc) concentration (1000-3000 ppm) and rotation
speed (1000-1500 rpm) on CO2 corrosion performance of the regression model
calculated by RSM. The experiments were conducted in saturated solution of CO2
with 3.5 % NaCl solution. STATISTICA program version 10 was used for data
analysis. In conclusion a quadratic model is proposed to predict the effect of
mentioned variables in CO2 environment.
different CO2 corrosion parameters conditions. Most of these models did not predict
the corrosion rate exactly, besides it determined effects of variables by holding some
variables constant and changing the values of other variables to obtain the regression
model. As a result the experiments will be large and cost too much. In this paper
response surface methodology (RSM) was proposed to optimize the experiments and
reduce the experimental running. The experiments studied effects of temperature (40
– 60 °C), pH (3-5), acetic acid (HAc) concentration (1000-3000 ppm) and rotation
speed (1000-1500 rpm) on CO2 corrosion performance of the regression model
calculated by RSM. The experiments were conducted in saturated solution of CO2
with 3.5 % NaCl solution. STATISTICA program version 10 was used for data
analysis. In conclusion a quadratic model is proposed to predict the effect of
mentioned variables in CO2 environment.