51313-02615-Dev. of Adaptive-Predictive Probabilistic Methodology to Forecast Localized-Corrosion-Induced Damage

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Product Number: 51313-02615-SG

ISBN: 02615 2013 CP

Author: Pavan Shukla

Publication Date: 2013

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This paper presents an adaptive-predictive probabilistic methodology for forecasting localized-corrosion-induced pit population and pit depth distributions. Nuclear power plant (NPP) operators are required to periodically inspect components by visual and volumetric examinations to maintain integrity and ensure safety. However as NPPs age more frequent inspections would be needed for maintaining component integrity. To define inspection schedules a framework is needed that balances risk and cost and ensures safety.

This paper presents a methodology including a model that could be used to predict localized corrosion-induced damage of NPP components. For example if a component is undergoing pitting corrosion in an environment the model predicts the pit population and the pit depth distribution as a function of time (i.e. the fraction of pits at a particular depth at a particular time). The methodology and associated model accounts for previous inspection data randomness of pit generation and propagation and pit growth rate as a function of time. The model results could be used to estimate probability of component failure due to pitting corrosion and thresholds for enhanced inspection schedules. The paper will also present data on pitting of stainless steel controlled conditions where and pit growth is monitored using non-destructive techniques such as eddy-current. Comparisons of model predictions to depths of experimental pit populations will be presented and predict estimates of pit depths.