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51314-4346-An Application of Adaptive-Predictive Probabilistic Methodology for Forecasting Localized-Corrosion-Induced Damage

Product Number: 51314-4346-SG
ISBN: 4346 2014 CP
Author: Pavan Shukla
Publication Date: 2014
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Title: An  Application of Adaptive-Predictive Probabilistic Methodology for Forecasting Localized-Corrosion-Induced DamageThis paper presents an application of an adaptive-predictive probabilistic model for forecasting localized-corrosion-induced pit population and pit depth distributions. The application involves predicting pitting corrosion damage in 304SS due to accumulation of sea salt.  This paper provides summary of follow on work from the previous paper which was presented in CORROSION 2013. Pitting corrosion was induced on several rectangular 304SS coupons by depositing the sea salt and placing the coupons at 50 degree C and 40 percent relative humidity environment.  One by one the coupons were removed from the environment.  These coupons were used to gather initial information regarding the pitting corrosion depth and population distribution.  This information was fed in the adaptive-predictive probabilistic model.  The output from the model was compared with the data collected from the coupons which were removed from the environment after making the prediction.  The model details the coupon data and a comparison between the forecasted pit depth and population distribution from the model and the coupon data will be presented.   
Title: An  Application of Adaptive-Predictive Probabilistic Methodology for Forecasting Localized-Corrosion-Induced DamageThis paper presents an application of an adaptive-predictive probabilistic model for forecasting localized-corrosion-induced pit population and pit depth distributions. The application involves predicting pitting corrosion damage in 304SS due to accumulation of sea salt.  This paper provides summary of follow on work from the previous paper which was presented in CORROSION 2013. Pitting corrosion was induced on several rectangular 304SS coupons by depositing the sea salt and placing the coupons at 50 degree C and 40 percent relative humidity environment.  One by one the coupons were removed from the environment.  These coupons were used to gather initial information regarding the pitting corrosion depth and population distribution.  This information was fed in the adaptive-predictive probabilistic model.  The output from the model was compared with the data collected from the coupons which were removed from the environment after making the prediction.  The model details the coupon data and a comparison between the forecasted pit depth and population distribution from the model and the coupon data will be presented.   
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