Aqueous Corrosion Testing and Neural Network Modeling to Simulate Corrosion of Supercritical CO2 Pipelines in the Carbon Capture and Storage Cycle

Sim, S, Cavanaugh, M, Corrigan, P, Cole, I and Birbilis, N 2013, 'Aqueous Corrosion Testing and Neural Network Modeling to Simulate Corrosion of Supercritical CO2 Pipelines in the Carbon Capture and Storage Cycle', Corrosion, vol. 69, no. 5, pp. 477-486.


Document type: Journal Article
Collection: Journal Articles

Title Aqueous Corrosion Testing and Neural Network Modeling to Simulate Corrosion of Supercritical CO2 Pipelines in the Carbon Capture and Storage Cycle
Author(s) Sim, S
Cavanaugh, M
Corrigan, P
Cole, I
Birbilis, N
Year 2013
Journal name Corrosion
Volume number 69
Issue number 5
Start page 477
End page 486
Total pages 10
Publisher N A C E International
Abstract A database was constructed from tests in aqueous electrolytes simulating the damage that may occur to ferrous transport pipelines in the carbon capture and storage (CCS) process. Temperature and concentrations of carbonic acid (H2CO3), sulfuric acid (H2SO4), hydrochloric acid (HCl), nitric acid (HNO3), sodium nitrate (NaNO3), sodium sulfate (Na2SO4), and sodium chloride (NaCl) were varied; the potentiodynamic polarization response, along with physical damage from exposure, was measured. Sensitivity analysis was conducted via generation of fuzzy curves, and a neural network model also was developed. A correlation between corrosion current (icorr) and exposure tests (measured in the form of weight and thickness loss) was observed; however, the key outcome of the work is the presentation of a model that captures corrosion rate as a function of environments relevant to (CCS) pipeline, revealing the extent of the threat and the variables of interest. © 2013, NACE International.
Subject Machine Tools
Keyword(s) Carbon capture and storage
Carbon dioxide
Carbonic acid
Corrosion
Neural network
Pipeline
Sulfuric
Supercritical
DOI - identifier 10.5006/0807
Copyright notice © 2013, NACE International.
ISSN 0010-9312
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