Menu
Search
Filters
Close
Menu

Developing A Likelihood-Based Modeling Approach To Predict Atmospheric Corrosion Rates Using Corrosion Sensor Technologies

Picture for Developing A Likelihood-Based Modeling Approach To Predict Atmospheric Corrosion Rates Using Corrosion Sensor Technologies
Available for download
Product Number: 51321-16806-SG
Author: Erin C. DeCarlo; James F. Dante; Erica N. Macha
Publication Date: 2021
$0.00
$20.00
$20.00

The current approach to corrosion severity prediction is to use long-term averages of environmental parameters (such as relative humidity, temperature, and pollutants), geographic features (such as coastal proximity), and witness coupon corrosion rates for indicator materials to classify an environment into one of a small number of severity categories. However, recent work has revealed that brief changes in environmental conditions-even those lasting only a few hours-can significantly affect total corrosion damage, and long-term averages of environmental conditions are not sufficient to accurately predict cumulative corrosion damage. Recent improvements in corrosion sensing technology have made corrosion sensors a possible replacement for-or at least an enhancement to-the severity classification approach. Recent modeling efforts have demonstrated that greater prediction accuracy is achieved using corrosion rate models trained under constant salt loads, such as those in between precipitation events. Thus, this paper first describes a novel likelihood-based salt load identification algorithm to improve long-term corrosion rate predictions across events that change surface salt loading densities by tracking salt loading characteristics on the sensor.  The developed likelihood­ based salt load identification algorithm is then used to weight corresponding corrosion rate prediction models trained using data collected from laboratory exposures of corrosion sensors for which the salt loading was controlled and periodically changed. The improvement in the corrosion rate and total corrosion damage predictions across exposures are evaluated for multiple sensors, salt loading densities, and exposures.

The current approach to corrosion severity prediction is to use long-term averages of environmental parameters (such as relative humidity, temperature, and pollutants), geographic features (such as coastal proximity), and witness coupon corrosion rates for indicator materials to classify an environment into one of a small number of severity categories. However, recent work has revealed that brief changes in environmental conditions-even those lasting only a few hours-can significantly affect total corrosion damage, and long-term averages of environmental conditions are not sufficient to accurately predict cumulative corrosion damage. Recent improvements in corrosion sensing technology have made corrosion sensors a possible replacement for-or at least an enhancement to-the severity classification approach. Recent modeling efforts have demonstrated that greater prediction accuracy is achieved using corrosion rate models trained under constant salt loads, such as those in between precipitation events. Thus, this paper first describes a novel likelihood-based salt load identification algorithm to improve long-term corrosion rate predictions across events that change surface salt loading densities by tracking salt loading characteristics on the sensor.  The developed likelihood­ based salt load identification algorithm is then used to weight corresponding corrosion rate prediction models trained using data collected from laboratory exposures of corrosion sensors for which the salt loading was controlled and periodically changed. The improvement in the corrosion rate and total corrosion damage predictions across exposures are evaluated for multiple sensors, salt loading densities, and exposures.

Product tags
Also Purchased
Picture for 00405 AN ADVANCED ATMOSPHERIC CORROSION
Available for download

00405 AN ADVANCED ATMOSPHERIC CORROSION MEASUREMENT SYSTEM

Product Number: 51300-00405-SG
ISBN: 00405 2000 CP
Author: Philippe Kempe, Allen Denzine, and Eugen Tiefnig
$20.00
Picture for 01544 THE EFFECTS OF WIND ON LOCAL ATMOSPHERIC
Available for download

01544 THE EFFECTS OF WIND ON LOCAL ATMOSPHERIC CORROSIVITY

Product Number: 51300-01544-SG
ISBN: 01544 2001 CP
Author: R.D. Klassen and P.R. Roberge
$20.00
Picture for Formation of Galvanic Cells and Localized Corrosion under Atmospheric Conditions
Available for download

51316-7212-Formation of Galvanic Cells and Localized Corrosion under Atmospheric Conditions

Product Number: 51316-7212-SG
ISBN: 7212 2016 CP
Author: Dominique Thierry
Publication Date: 2016
$20.00

The aim of this study was to determine the mechanism of atmospheric corrosion of zinc in areas of local NaCl contamination and to define the driving force of spreading of electrochemical reactions using Scanning Kelvin Probe (SKP).
Categories
Industry
Recently viewed
Popular tags
View all

Association for Materials Protection and Performance

© AMPP All Rights Reserved.
Membership Terms of Content Use
Contact Customer Support