Techniques for Improved Reliability of Wall Thinning Estimation

2006 ◽  
Author(s):  
Yogendra S. Garud
Keyword(s):  
The Other ◽  
Remaining Life ◽  
Data Filtering ◽  
Large Database ◽  
Accelerated Corrosion ◽  
Wall Thinning ◽  
Simplified Method ◽  
Flow Accelerated Corrosion ◽  
The Impact ◽  
Thinning Rate

Wall thinning in pressure retaining components, especially due to the flow-accelerated corrosion, has been a significant factor affecting the safety and unplanned system downtimes. On the other hand, overestimating the impact of possible wall thinning often leads to unnecessary or expensive inspections and replacements. The simplified or quick (short-cut) methods of analysis and prediction often lack the requisite degree of accuracy and confidence. This paper presents a few techniques for better analysis of the wall thinning data to address these issues. These techniques make use of the statistical methods, pattern recognition, and optimization to perform a robust data filtering and thinning rate estimation that accounts for measurement uncertainty. The techniques are discussed with application to a large database and an inspection program. The impact of these analytical improvements is presented in comparison with results of the simplified method of analysis. The results include both the margin on remaining life and the projected wall thinning rates, with implications for inspections.

The Impact of Flow Accelerated Corrosion (FAC) on Feeder Life Cycle Management

2009 ◽  
Author(s):  
Mahesh D. Pandey ◽  
Mikko I. Jyrkama ◽  
Edward M. Lehockey
Keyword(s):  
Life Cycle ◽  
Wall Thickness ◽  
Safety Concern ◽  
Probabilistic Method ◽  
Life Cycle Management ◽  
Economic Losses ◽  
Accelerated Corrosion ◽  
Wall Thinning ◽  
Flow Accelerated Corrosion ◽  
The Impact

Wall thinning of outlet feeder piping by flow accelerated corrosion (FAC) is a serious form of degradation affecting some CANDU® stations. The general and localized loss of wall thickness is typically highest at or near welds and changes in pipe geometry due to increased velocity or turbulence. While the process is not a high safety concern because catastrophic failure is unlikely, feeder wall thinning may result in significant economic losses as a result of forced shutdowns for repair and replacement. Accurate modelling and prediction of feeder replacements and the probability of feeder failure is not only important for continued fitness-for-service, but essential for feeder life cycle management (LCM). This paper discusses some of the key issues related to feeder FAC, and presents a probabilistic method for modelling the wall thinning process. The wall thickness loss due to FAC is modelled using a random rate model, while the probability of feeder failure is based on an empirical approach. The developed methodology allows the estimation of the remaining life of both inspected and uninspected feeder populations, while methodically accounting for the uncertainties in the problem.

Evaluation of Wall Thinning Rate Due to Flow Accelerated Corrosion With the Coupled Models of Electrochemical Analysis and Double Oxide Layer Analysis

2009 ◽  
Author(s):  
Masanori Naitoh ◽  
Shunsuke Uchida ◽  
Yasushi Uehara ◽  
Hidetoshi Okada ◽  
Seiichi Koshizuka
Keyword(s):  
Oxide Layer ◽  
Electrochemical Analysis ◽  
Anodic Current Density ◽  
Coupled Models ◽  
Accelerated Corrosion ◽  
Double Oxide ◽  
Wall Thinning ◽  
Layer Analysis ◽  
Flow Accelerated Corrosion ◽  
Thinning Rate

Systematic approaches for evaluating flow accelerated corrosion (FAC) are desired before discussing application of countermeasures for FAC. Future FAC occurrence should be evaluated to identify locations where a higher possibility of FAC occurrence exists, and then, wall thinning rate at the identified FAC occurrence zone should be evaluated to obtain the preparation time for applying countermeasures. Wall thinning rates were calculated with the coupled models of static electrochemical analysis and dynamic double oxide layer analysis. Anodic current density and electrochemical corrosion potential (ECP) were calculated with the electrochemistry model based on an Evans diagram and ferrous ion release rate determined by the anodic current density was applied as input for the double oxide layer model. The thickness of oxide layer was calculated with the double oxide layer model. The dependences of mass transfer coefficients, oxygen concentrations ([O2]), pH and temperature on wall thinning rates were calculated with the coupled model. It was confirmed that the calculated results of the coupled models resulted good agreement with the measured ones. The effects of candidates for countermeasures, e.g., optimization of N2H4 injection point into the feed water system, on FAC mitigation was demonstrated as a result of applying the model.

A Statistical Model for Accessing Wall Thinning Rate due to Flow Accelerated Corrosion Based on Inspection Data in Nuclear Power Plants

2014 ◽  
Author(s):  
Yuyun Zeng ◽  
Jingquan Liu ◽  
Weilin Huang
Keyword(s):  
Statistical Model ◽  
Nuclear Power ◽  
Power Plants ◽  
Nuclear Power Plants ◽  
Lifetime Distributions ◽  
Accelerated Corrosion ◽  
Wall Thinning ◽  
Inspection Data ◽  
Flow Accelerated Corrosion ◽  
Thinning Rate

Flow accelerated corrosion (FAC) is a major degradation form of carbon steel and low alloy pipes in the secondary circuit of pressurized water reactor (PWR) plants, which has great impact on plant safety and reliability. For the purpose of effectively monitoring FAC in nuclear power plants, a statistical model for accessing FAC wall thinning rate using plant inspection data is proposed in this paper. The presented model is developed based on Gaussian stochastic process models. Wall thinning rate is considered as a function of key factors that have important influence on the FAC process (i.e., temperature, pH, mass transfer coefficient, etc.). The Kriging method, which has been widely applied in the domain of spatial analysis, is used to model the relationship between wall thinning rate and its impact factors. Model parameters are determined through maximum likelihood estimation using the inspection data. Since the likelihood function of the Kriging model is usually complicated in form, the genetic algorithm is employed to find parameter values that maximize this function. From the presented model, residual lifetime distributions of pipes affected by FAC can be derived, and conditions that may lead to high FAC rate can be found, which provides decision-making support for maintenance strategies optimization in life cycle management of the feed water system. Wall thinning data simulated from a physical-chemical mechanism model presented in literature are used to verify the presented model. Results of validation show that reasonable wall thinning rates and lifetime distributions can be obtained using this model.

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