• Nuclear Engineering and Technology
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• v.36 no.4
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• pp.327-337
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• 2004

It is commonly required that tubes with defects exceeding $40\%$ of wall thickness in depth should be plugged; however, this criterion is too conservative for some locations and for some types of defects. Many studies have been done with the aim of developing an alternative plugging criteria, and these studies have shown that steam generator tubes with a certain range of axial through-wall cracks could remain in service without any safety or reliability problems. However, these studies have been limited, thus far, to consideration of single cracked tubes, necessitating a study on multiple cracks, which are commonly found. A crack coalescence model applicable to steam generator tubes with two collinear axial through-wall cracks was proposed in the previous study. In this paper, the investigation is extended to the parallel axial cracks spaced in a circumferential direction, because parallel axial cracks are more frequently detected during in-service inspections than collinear axial cracks. Interaction effects between two parallel cracks are evaluated by performing elastic and elastic-plastic finite element analyses.

• Nuclear Engineering and Technology
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• v.50 no.1
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• pp.88-96
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• 2018

Concerns over reliability assessments of the main components in nuclear power plants (NPPs) related to aging and continuous operation have increased. The conventional reliability assessment for main components uses experimental correlations under general conditions. Most NPPs have been operating in Korea for a long time, and it is predictable that NPPs operating for the same number of years would show varying extent of aging and degradation. The conventional reliability assessment does not adequately reflect the characteristics of an individual plant. Therefore, the reliability of individual components and an individual plant was estimated according to operating data and conditions. It is essential to reflect aging as a characteristic of individual NPPs, and this is performed through prognostics. To handle this difficulty, in this paper, the general path model/Bayes, a data-based prognostic method, was used to update the reliability estimated from the generic database. As a case study, the authors consider the aging for steam generator tubes in NPPs and demonstrate the suggested methodology with data obtained from the probabilistic algorithm for the steam generator tube assessment program.

• Nuclear Engineering and Technology
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• v.52 no.11
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• pp.2565-2571
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• 2020

Background: Understanding the behaviour of nuclear fuel claddings by conducting burst test on single cladding tube under simulated loss-of-coolant accident conditions and developing theoretical cum empirical predictive computer codes have been the focus of several investigations. The developed burst criterion (a) assumes symmetrical deformation of cladding tube in contrast to experimental observation (b) interpolates the properties of Zircaloy-4 cladding in mixed α+β phase (c) does not account for azimuthal temperature variations. In order to overcome all these drawbacks of burst criterion, it is reasoned that artificial intelligence technique may be a better option to predict the burst parameters. Methods: Artificial neural network models based on feedforward backpropagation algorithm with logsig transfer function are developed. Results: Neural network architecture of 2-4-4-3, that is model with two hidden layers having four nodes in each layer is found to be the most suitable. The mean, maximum, and minimum prediction errors for this optimised model are 0.82%, 19.62%, and 0.004%, respectively. Conclusion: The burst stress, burst temperature, and burst strain obtained from burst criterion have average deviation of 19%, 12%, and 53% respectively whereas the developed neural network model predicted these parameters with average deviation of 6%, 2%, and 8%, respectively.

• Nuclear Engineering and Technology
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• v.45 no.2
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• pp.265-276
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• 2013

Pressure tubes made of Zr-2.5 wt% Nb alloy are important components consisting reactor coolant pressure boundary of a pressurized heavy water reactor, in which unanticipated through-wall cracks and rupture may occur due to a delayed hydride cracking (DHC). The Canadian Standards Association has provided deterministic and probabilistic structural integrity evaluation procedures to protect pressure tubes against DHC. However, intuitive understanding and subsequent assessment of flaw behaviors are still insufficient due to complex degradation mechanisms and diverse influential parameters of DHC compared with those of stress corrosion cracking and fatigue crack growth phenomena. In the present study, a deterministic flaw assessment program was developed and applied for systematic integrity assessment of the pressure tubes. Based on the examination results dealing with effects of flaw shapes, pressure tube dimensional changes, hydrogen concentrations of pressure tubes and plant operation scenarios, a simple and rough method for effective cooldown operation was proposed to minimize DHC risks. The developed deterministic assessment program for pressure tubes can be used to derive further technical bases for probabilistic damage frequency assessment.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.12
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• pp.1995-2001
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• 2001

In this study, a small punch creep(SP-Creep) test using miniaturized specimen(10${\times}$10${\times}$0.5mm) is described to develop the new creep test method for high temperature structural materials. The SP-Creep test is applied to 2.25Cr-lMo(STBA24) steel which is widely used as boiler tube material. The test temperatures applied for the creep deformation of miniaturized specimens are between 550∼600$^{\circ}C$. The SP-Creep curves depend definitely on applied load and creep temperature, and show the three stages of creep behavior like in conventional uniaxial tensile creep curves. The load exponent of miniaturized specimen decreases with increasing test temperature, and its behavior is similar to stress exponent behavior of uniaxial creep test. The creep activation energy obtained from the relationship between SP-Creep rate and test temperature decreases as the applied load increases. A predicting equation or SP-Creep rate for 2.25Cr-lMo steel is suggested. and a good agreement between experimental and calculated data has been found.

• Nuclear Engineering and Technology
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• v.28 no.5
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• pp.467-481
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• 1996

An integrated framework of modeling the human operator cognitive behavior during nuclear power plant accident scenarios is presented. It incorporates both plant and operator models. The basic structure of the operator model is similar to that of existing cognitive models, however, this model differs from those existing ones largely in too aspects. First, using frame and membership function, the pattern matching behavior, which is identified as the dominant cognitive process of operators responding to an accident sequence, is explicitly implemented in this model. Second, the non-task-related human cognitive activities like effect of stress and cognitive biases such as confirmation bias and availability bias, are also considered. A computer code, OPEC is assembled to simulate this framework and is actually applied to an SGTR sequence, and the resultant simulated behaviors of operator are obtained.

• Journal of Ocean Engineering and Technology
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• v.12 no.2 s.28
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• pp.71-78
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• 1998

In this report for the assessment of creep properties of high-temperature tube materials in power plants, the long-time($10^4$~105h) creep life prediction by ISM for 2.25Cr1Mo steel was studied. It was clarified experimentally and quantitatively that the newly developed long-time creep life prediction equation was very coincident with the actual experimental data with high confidence, and the model was $t_r=\alpha\varepsilon_0^{\beta}\sigma^{-1}$.

• Nuclear Engineering and Technology
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• v.49 no.2
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• pp.313-326
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• 2017

The systematic management of plant risk is crucial for enhancing the safety of nuclear power plants and for designing new nuclear power plants. Accident sequence precursor (ASP) analysis may be able to provide risk significance of operational experience by using probabilistic risk assessment to evaluate an operational event quantitatively in terms of its impact on core damage. In this study, an ASP methodology for two operation mode, full power and low power/shutdown operation, has been developed and applied to significant accident precursors that may occur during the operation of nuclear power plants. Two operational events, loss of feedwater and steam generator tube rupture, are identified as ASPs. Therefore, the ASP methodology developed in this study may contribute to identifying plant risk significance as well as to enhancing the safety of nuclear power plants by applying this methodology systematically.

• Nuclear Engineering and Technology
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• v.50 no.4
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• pp.582-588
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• 2018

Accident diagnosis is one of the complex tasks for nuclear power plant (NPP) operators. In abnormal or emergency situations, the diagnostic activity of the NPP states is burdensome though necessary. Numerous computer-based methods and operator support systems have been suggested to address this problem. Among them, the recurrent neural network (RNN) has performed well at analyzing time series data. This study proposes an algorithm for accident diagnosis using long short-term memory (LSTM), which is a kind of RNN, which improves the limitation for time reflection. The algorithm consists of preprocessing, the LSTM network, and postprocessing. In the LSTM-based algorithm, preprocessed input variables are calculated to output the accident diagnosis results. The outputs are also postprocessed using softmax to determine the ranking of accident diagnosis results with probabilities. This algorithm was trained using a compact nuclear simulator for several accidents: a loss of coolant accident, a steam generator tube rupture, and a main steam line break. The trained algorithm was also tested to demonstrate the feasibility of diagnosing NPP accidents.

• Nuclear Engineering and Technology
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• v.44 no.4
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• pp.415-420
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• 2012

It is important to understand the amount of time required to execute an emergency procedural task in a high-stress situation for managing human performance under emergencies in a nuclear power plant. However, the time to execute an emergency procedural task is highly dependent upon expert judgment due to the lack of actual data. This paper proposes an analytical method to estimate the operator's performance time (OPT) of a procedural task, which is based on a measure of the task complexity (TACOM). The proposed method for estimating an OPT is an equation that uses the TACOM as a variable, and the OPT of a procedural task can be calculated if its relevant TACOM score is available. The validity of the proposed equation is demonstrated by comparing the estimated OPTs with the observed OPTs for emergency procedural tasks in a steam generator tube rupture scenario.