• Nuclear Engineering and Technology
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• v.52 no.9
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• pp.2119-2129
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• 2020

Flow-accelerated corrosion (FAC), liquid droplet impingement erosion (LDIE), cavitation and flashing can cause continuous wall-thinning in nuclear secondary pipes. In order to prevent pipe rupture events resulting from the wall-thinning, most NPPs (nuclear power plants) implement their management programs, which include periodic thickness inspection using UT (ultrasonic test). Meanwhile, it is well known in field experiences that the thickness measurement errors (or deviations) are often comparable with the amount of thickness reduction. Because of these errors, it is difficult to estimate wall-thinning exactly whether the significant thinning has occurred in the inspected components or not. In the previous study, the authors presented an approximate estimation procedure as the first step for thickness measurement deviations at each inspected component and the statistical & quantitative characteristics of the measurement deviations using plant experience data. In this study, statistical significance was quantified for the current methods used for wall-thinning determination. Also, the authors proposed new estimation procedures for determining local wall-thinning to overcome the weakness of the current methods, in which the proposed procedure is based on analysis of variance (ANOVA) method using subgrouping of measured thinning values at all measurement grids. The new procedures were also quantified for their statistical significance. As the results, it is confirmed that the new methods have better estimation confidence than the methods having used until now.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.5 s.248
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• pp.533-542
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• 2006

In order to assess the integrity of pipes with local thinning area, the plastic strain as well as the elastic strain at the root of thinned region are required particularly when fluctuating load is applied to the pipe. For estimating elastic-plastic strain at local wall thinning area in a straight pipe under tensile load, an estimation model with idealized fully circumferential constant depth wall thinning area is proposed. Based on the compatibility and equilibrium equations a nonlinear estimation equation, from which local elastic-plastic strain can be determined as a function of pipe/defect geometry, material and the applied strain was derived. Estimation results are compared with those from detailed elastic-plastic finite element analysis, which shows good agreements. Noting that practical wall thinning in nuclear piping has not only a circular shape but also a finite circumferential length, the proposed solution for the ideal geometry is extended based on two-dimensional and three-dimensional numerical analysis of pipes with circular wall thinning.

• Nuclear Engineering and Technology
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• v.55 no.3
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• pp.947-957
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• 2023

Curved cylindrical structures such as elbows have a non-uniform thickness distribution due to their fabrication process, and as a result have a number of complex mode shapes, including circumferential and axial nodal patterns. In nuclear power plants, material degradation is induced in pipes by flow accelerated erosion and corrosion, causing the wall thickness of carbon steel elbows to gradually thin. The corresponding frequencies of each mode shape vary according to the wall thinning state. Therefore, the thinning state can be estimated by monitoring the varying modal characteristics of the elbow. This study investigated the varying modal characteristics of artificially thinned carbon steel elbows for each thinning state using numerical simulation and experimental methods (MRIT, Multiple Reference Impact Test). The natural frequencies of specified mode shapes were extracted, and results confirmed they linearly decreased with increasing thinning. In addition, by comparing single FRF (Frequency Response Function) data with the results of MRIT, a concise and cost effective thinning estimation method was suggested.

• Nuclear Engineering and Technology
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• v.52 no.11
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• pp.2678-2685
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• 2020

The pipe bends and elbows in nuclear power plants (NPPs) are vulnerable to degradation mechanisms and can cause wall-thinning defects. As it is difficult to detect both the defects generated inside the wall-thinned pipes and the preliminary signs, the wall-thinning defects should be accurately estimated to maintain the integrity of NPPs. This paper proposes a deep fuzzy neural network (DFNN) method and estimates the collapse moment of wall-thinned pipe bends and elbows. The proposed model has a simplified structure in which the fuzzy neural network module is repeatedly connected, and it is optimized using the least squares method and genetic algorithm. Numerical data obtained through simulations on the pipe bends and elbows with extrados, intrados, and crown defects were applied to the DFNN model to estimate the collapse moment. The acquired databases were divided into training, optimization, and test datasets and used to train and verify the estimation model. Consequently, the relative root mean square (RMS) errors of the estimated collapse moment at all the defect locations were within 0.25% for the test data. Such a low RMS error indicates that the DFNN model is accurate in estimating the collapse moment for wall-thinned pipe bends and elbows.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2008.06a
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• pp.701-702
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• 2008

• Proceedings of the Korean Nuclear Society Conference
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• 1999.05a
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• pp.227-227
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• 1999

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.3 s.258
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• pp.304-312
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• 2007

The objective of this study is to develop a local failure criterion for a wall thinning defect of piping components. For this purpose, a series of tensile tests was performed using several types of simulated specimens with different stress states, including smooth round bar, notched round bar (five different notch radii), and grooved plate (three different groove radii). In addition, finite element (FE) simulations were performed on the simulated specimen tests and the results were compared with the test results. From the comparisons, the equivalent stress and strain corresponding to maximum load and final failure of notched specimens were proposed as failure criteria under tensile load. The criteria were verified by employing them to the estimation of failure of grooved plate specimens that simulate the wall thinning defect. It showed that the proposed criteria accurately estimate the maximum load and final failure of grooved plate specimen tests.

• Journal of the Korean Society for Nondestructive Testing
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• v.24 no.4
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• pp.362-370
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• 2004

In this work, the collapse moment due to wall-thinning defects is estimated by using fuzzy neural networks. The developed fuzzy neural networks have been applied to the numerical data obtained from the finite element analysis. Principal component analysis is used to preprocess the input signals into the fuzzy neural network to reduce the sensitivity to the input change and the fuzzy neural networks are trained by using the data set prepared for training (training data) and verified by using another data set different (independent) from the training data. Also, two fuzzy neural networks are trained for two data sets divided into the two classes of extrados and intrados defects, which is because they have different characteristics. The relative 2-sigma errors of the estimated collapse moment are 3.07% for the training data and 4.12% for the test data. It is known from this result that the fuzzy neural networks are sufficiently accurate to be used in the wall-thinning monitoring of elbows.

• Nuclear Engineering and Technology
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• v.35 no.2
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• pp.144-153
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• 2003

The object of this paper is the probabilistic failure analysis on the cladding performance of WPF(Whole Pin Furnace) test fuel pins under transient conditions, and analysis of the KALIMER fuel pin using the preceding analysis. The cumulative damage estimation and Weibull probability estimation of WPF test are performed. The probabilistic method was adapted for these analyses to determine the effective thickness thinning due to eutectic penetration depth. In the results, it is difficult to assume that a brittle layer depth made by eutectic reaction is all of the thickness reduction due to cladding thinning. About 93% cladding thinning of the eutectic penetration depth is favorable as an effective thickness of cladding. And the unreliability of the KALIMER driver fuel pin under the same WPF test condition is lower than that of the WPF pin because of the higher plenum-fuel volume ratio and lower cladding inner radius vs. thickness ratio. KALIMER fuel pin developed from conceptual design has a more stable transient performance for a failure mechanism due to fission gas buildup than the WPF pin.

• Corrosion Science and Technology
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• v.11 no.4
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• pp.129-134
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• 2012

UT(Ultrasonic Test), one of the non-destructive tests, is the most common thickness measurement method for evaluating the wear rate in NPPs(Nuclear Power Plants). UT is used widely because it is easy and safe for use. However some amount of error inevitably occurs in attempting to measure the thickness. The error, that could make the thickness data thicker or thinner, may affect estimation of wear rate in pipes. NPPs are composed of a lot of pipes and components. Some of them are tested to check the current status during RFO(Re-Fueling Outage). Reliability analysis of UT is essential for evaluating pipe wear rate and establishing the long-term management plan in NPPs. This paper reviewed the cause of error occurrence and presented the UT data reliability analysis method. Also, this paper shows the application result of reliability analysis to the UT data acquired in NPPs.