Analyses corrosion prediction software for CO2 corrosion of carbon steel using statistical formulas
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 pred...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
International Journal of Mechanical Engineering and Robotics Research
2019
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| Subjects: | |
| 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 |
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| Summary: | 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 |
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