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Analyses Corrosion Prediction Software for CO2 Corrosion of Carbon Steel Using Statistical Formulas

Y. P. Asmara, A. G. E. Sutjipto, J. P. Siregar, T. Kurniawan, Jamiluddin Jaafar
Faculty of Mechanical Engineering, Universiti Malaysia Pahang
Faculty of Science and Technology Industry, Universiti Malaysia Pahang, Pahang, Malaysia

Abstract—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, CO2 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. 

Index Terms—CO2 Corrosion, carbon steel, corrosion models

Cite: Y. P. Asmara, A. G. E. Sutjipto, J. P. Siregar, T. Kurniawan, Jamiluddin Jaafar, "Analyses Corrosion Prediction Software for CO2 Corrosion of Carbon Steel Using Statistical Formulas," International Journal of Mechanical Engineering and Robotics Research, Vol. 8, No. 3, pp. 374-379, May 2019. DOI: 10.18178/ijmerr.8.3.374-379

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