Analyses corrosion prediction software for CO2 corrosion of carbon steel using statistical formulas

• Main Authors: Asmara, Y. P., Sutjipto, A. G. E., Siregar, J. P., Kurniawan, Tedi, Jamiluddin, Jaafar
• Format: Article
• Language: English
• Published: International Journal of Mechanical Engineering and Robotics Research 2019
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://umpir.ump.edu.my/id/eprint/25500/1/2019%2C%20YP%20Asmara%20et.%20al.%2C%20Analyses%20Corrosion%20Prediction%20Software%20for%20CO2.pdf; http://umpir.ump.edu.my/id/eprint/25500/; https://doi.org/10.18178/ijmerr.8.3.374-379
• Institution: Universiti Malaysia Pahang

The statistical formulas are capable tools to find a regression of corrosion rate effectively among combining factors. One type of statistical model which is response surface methodology (RSM) has shown a proven method in minimizing number of running. Through this technique, this research study predicting corrosion rate of carbon steel as effects of pH, CO 2 pressure and temperature. It can be used to run 3 dependent factors, 3 level experiment with only 16 number of running. The result reveals that NORSOK corrosion prediction software with second order model regression has 98 % of coefficient determination. Model prediction of Cassandra has 99.3% of coefficient determination. Second order model also has been verified with experimental data which shows a good correlation