Development of wall thinning screening system and its application to a commercial nuclear power plant

A pipe-wall thinning measurement is a key inspection to ensure the integrity of the piping system in nuclear power plants. To monitor the integrity of the piping system, a number of ultrasonic thickness measurements are manually performed during the outage of the nuclear power plant. Since most of the pipes are covered with an insulator, removing the insulator is necessary for the ultrasonic thickness measurement. Noncontact ultrasonic sensors enable ultrasonic thickness inspection without removing the insulator. This leads to reduction of the inspection time and reduced radiation exposure of the inspector. The inductively-coupled transducer system (ICTS) is a noncontact ultrasonic sensor system which uses electromagnetic induction between coils to drive an installed transducer. In this study, we investigated the applicability of an innovative ICTS developed at the University of Bristol to nuclear power plant inspection, particularly pipe-wall thinning inspection. The following experiments were performed using ICTS: thickness measurement performance, the effect of the coil separation, the effect of the insulator, the effect of different inspection materials, the radiation tolerance, and the measurement accuracy of wastage defects. These initial experimental results showed that the ICTS has the possibility to enable wall-thinning inspection in nuclear power plants without removing the insulator. Future work will address the issue of measuring wall-thinning in more complex pipework geometries and at elevated temperatures.

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Probabilistic Fracture Assessment of Wall Thinning Pipe

Volume 6: Materials and Fabrication ◽

10.1115/pvp2005-71151 ◽

2005 ◽

Cited By ~ 2

Author(s):

Hideo Machida ◽

Kotoji Ando

Keyword(s):

Power Plant ◽

Nuclear Power Plant ◽

Probability Density Function ◽

Wear Rate ◽

Probability Density ◽

Density Function ◽

Failure Probability ◽

Nuclear Power ◽

Published Data ◽

Wall Thinning

This paper describes failure probability assessment of thinning pipe of a nuclear-power plant. The rupture of the feed water piping in the turbine building due to wall thinning happened in Kansai Electric Power Company (KEPCO) Mihama nuclear power plant Unit-3 on August 9, 2004. The variation between the prediction and measured wear rate was evaluated using the published data from KEPCO, and the probability density function was created. Using this probability density function, the failure probability of wall thinning pipe was evaluated using Monte Carlo simulation. The parameters of this evaluation are thinning patterns, wear rate, an applied stress and an inspection interval. The requirements to the inspection were clarified from the probability of failure.

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Development of wall-thinning evaluation procedure for nuclear power plant piping - Part 2: Local wall-thinning estimation method

Nuclear Engineering and Technology ◽

10.1016/j.net.2020.03.001 ◽

2020 ◽

Vol 52 (9) ◽

pp. 2119-2129 ◽

Cited By ~ 1

Author(s):

Hun Yun ◽

Seung-Jae Moon ◽

Young-Jin Oh

Keyword(s):

Power Plant ◽

Nuclear Power Plant ◽

Nuclear Power ◽

Estimation Method ◽

Evaluation Procedure ◽

Wall Thinning ◽

Local Wall Thinning

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Development of Wall-Thinning Evaluation Procedure for Nuclear Power Plant Piping—Part 1: Quantification of Thickness Measurement Deviation

Nuclear Engineering and Technology ◽

10.1016/j.net.2016.01.020 ◽

2016 ◽

Vol 48 (3) ◽

pp. 820-830 ◽

Cited By ~ 7

Author(s):

Hun Yun ◽

Seung-Jae Moon ◽

Young-Jin Oh

Keyword(s):

Power Plant ◽

Nuclear Power Plant ◽

Nuclear Power ◽

Thickness Measurement ◽

Evaluation Procedure ◽

Wall Thinning ◽

Measurement Deviation

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Uncertainty Assessment of Component Degradation Model Based on Support Vector Regression

Volume 1: Operations and Maintenance, Aging Management and Plant Upgrades; Nuclear Fuel, Fuel Cycle, Reactor Physics and Transport Theory; Plant Systems, Structures, Components and Materials; I&C, Digital Controls, and Influence of Human Factors ◽

10.1115/icone24-61114 ◽

2016 ◽

Author(s):

Chunzhen Yang ◽

Jingquan Liu ◽

Yuyun Zeng ◽

Muhammad Saeed

Keyword(s):

Power Plant ◽

Nuclear Power Plant ◽

Support Vector Regression ◽

Nuclear Power ◽

Support Vector ◽

Support Vector Regression Model ◽

Degradation Model ◽

Wall Thinning ◽

Modeling Uncertainties ◽

Test Sets

Degradation modeling and condition assessment of critical components are important issues in the maintenance of nuclear power plant, but modeling uncertainties must be taken into account seriously by considering the stochastic nature of degradation and observation process. Based on support vector regression algorithm, this article proposes a wall thinning model for carbon steel pipes in a nuclear power plant using in-service inspections data and further performs the uncertainty quantitive assessment for the proposed model. In the beginning, Latin hypercube sampling method is used to create new sample sets from the original observation with certain distribution of the mean values which are assumed from the observed data. Furthermore, part of the reconstructed sample sets are chosen as training sets to develop a wall thinning model and the remaining samples are used as test sets to verify the model. By comparing model predicted wall thickness values of the test sets and the observed values, a quantitative assessment of the degradation model uncertainty is obtained. The obtained results demonstrate that the deviations between observed thickness values and average model predicted values fluctuate around 1%, while model predicting variances are much smaller than the observed variances. This report concludes that the proposed support vector regression model for component degradation can provide accurate condition assessments with rather small variance.

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