Predictive Models for the Determination of Pitting Corrosion Versus Inhibitor Concentrations and Temperature for Radioactive Sludge in Carbon Steel Waste Tanks

Journal Article · Tue Oct 06 04:00:00 EDT 1998 · Corrosion Journal

OSTI ID:4899

Mickalonis, J I

Statistical models have been developed to predict the occurrence of pitting corrosion in carbon steel waste storage tanks exposed to radioactive nuclear waste. The levels of nitrite concentrations necessary to inhibit pitting at various temperatures and nitrate concentrations were experimentally determined via electrochemical polarization and coupon immersion corrosion tests. Models for the pitting behavior were developed based on various statistical analyses of the experimental data. Feed-forward Artificial Neural Network (ANN) models, trained using the Back-Propagation of Error Algorithm, more accurately predicted conditions at which pitting occurred than the logistic regression models developed using the same data.

• Research Organization: Savannah River Site
• Sponsoring Organization: DOE
• DOE Contract Number: AC09-96SR18500
• OSTI ID: 4899
• Report Number(s): WSRC-MS-98-00653
• Journal Information: Corrosion Journal, Journal Name: Corrosion Journal
• Country of Publication: United States
• Language: English

Related Subjects

05 NUCLEAR FUELS
36 MATERIALS SCIENCE
Abundance
Carbon Steels
Corrosion Inhibition
Mathematical Models
Nitrates
Nitrites
Radioactive Waste Storage
Tanks
Temperature Dependence