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...
| 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://eprints.uthm.edu.my/7158/ http://eprints.uthm.edu.my/7158/1/J14208_f2ea060f53dd6e7ae3a94a8cc5201855.pdf |
| 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, 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. |
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