A Statistics Approach for the Prediction of CO2 Corrosion in Mixed Acid Gases
Predicting CO2 corrosion is an important element in Corrosion Design Basis (CDB) which determines material selection and corrosion control strategies. Since CO2 corrosion is a multi species corrosion mechanism, there are numerous corrosion prediction models developed with different parameters....
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
2009
|
| Subjects: | |
| Online Access: | http://scholars.utp.edu.my/id/eprint/1846/ http://scholars.utp.edu.my/id/eprint/1846/1/Corrosion%26Materials.pdf |
| Summary: | Predicting CO2 corrosion is an important element in
Corrosion Design Basis (CDB) which determines material
selection and corrosion control strategies. Since CO2
corrosion is a multi species corrosion mechanism, there
are numerous corrosion prediction models developed with
different parameters. However, most of these prediction
models do not consider the combined effect of mixed
gases containing CO2, H2S and acetic acid (HAc) which
limits the corrosion prediction scope. This study analyzes
the effects of mixed gases by using Electronic Corrosion
Engineer (ECE®) corrosion prediction software combined
with a Response Surface Methodology (RSM) statistical
technique. ECE® prediction shows that simultaneous
effects of mixed gases behave differently as compared
to the individual effects. Contrast behavior was observed
for H2S as an individual species and as a mixed species;
corrosion rate depends on concentration level of H2S.
HAc species showed a sharper increase in corrosion in a
mixture than alone. This preliminary analysis of mixed gas
prediction showed multiple mechanisms. Thus, complex
interactions of mixed gases must be studied in more detail
to obtain an accurate prediction. |
|---|