• Journal of Intelligence and Information Systems
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• v.3 no.2
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• pp.1-9
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• 1997

These papers propose an evolutionary algorithm for re-using output of waste fuel of light water reactor system in nuclear power plants. Evolutionary algorithm is useful for optimization of the large space problem. The wastes contain several re-useable elements, and they should be carefully selected and blended to satisfy requirements as input material to the heavy water nuclear reactor system. This problem belongs to a NP-hard like the 0/1 Knapsack problem. Two evolutionary strategies are used as a, pp.oximation algorithms in the highly constrained combinatorial optimization problem. One is the traditional strategy, using random operator with evaluation function, and the other is heuristic based search that uses the vector operator reducing between goal and current status. We also show the method, which performs the feasible teat and solution evaluation by using the vectorized data in problem. Finally, We compare the simulation results of using random operator and vector operator for such combinatorial optimization problems.

• Transactions of the Korean Society of Pressure Vessels and Piping
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• v.5 no.2
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• pp.35-39
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• 2009

In this study, Event Type Analysis System (ETAS) is developed for the accident evaluation in nuclear power plant. The ETAS system can be used in supporting regulator and/or operator under event situation in nuclear power plants. The ETAS system can categorize the all transient events to 3 categories such as Down-2000, Down-2173, and Slow Fluctuation. We develop the program structure for ETAS system and web-based ETAS system. The ETAS system will be used as sub module of Knowledge-Based Event Evaluation Network (K-EvENT) which is developing for the against the accident in nuclear power plants.

• Nuclear Engineering and Technology
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• v.38 no.6
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• pp.551-560
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• 2006

In this study, a controller for a nuclear reactor power is designed. The reactor is modeled using the three dimensional reactor design code MASTER. From the relationship of the input and output of the reactor code, a reactor dynamic model is derived by the system identification method. This model is more realistic than the one based on mathematical theories. With this model, a robust controller is designed by the extended frequency response method. As this method has the same theoretical background as the classical method, all of the existing design techniques of the classical method can be used directly. Furthermore, by introducing the real part of a Laplacian operator into the frequency response, the control design specification can be considered at the initial stage of design. The designed controller is simple, and gives a sufficient robustness with good performance.

• Nuclear Engineering and Technology
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• v.39 no.6
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• pp.691-696
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• 2007

Nuclear energy programs around the world increasingly find themselves at the nexus of potentially conflicting demands from both domestic and international stakeholders. On one side, the rapid growth in demand for electricity coupled with the goal of reducing carbon emissions calls for a significant expansion of nuclear energy. On the other, stakeholders are seeking ever greater safety, environmental, security, and nonproliferation assurances before consenting to the construction of new nuclear energy facilities. Satisfying the demand for clean energy supplies will require nuclear energy operators to find new and innovative ways to build confidence among stakeholders. This paper discusses two related concepts which can contribute to meeting the needs of key stakeholders in cost effective and efficient ways. Structured processes and tools for assessing stakeholder needs can build trust and confidence while facilitating the "designing-in" of information collection systems for new facilities to achieve maximum efficiency and effectiveness. Integrated approaches to monitoring facilities and managing the resulting data can provide stakeholders with continued confidence while offering operators additional facility and process information to improve performance.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.2
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• pp.178-186
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• 2002

The objective of this study is to evaluate impact of computer-based man-machine interfaces of Korea Next Generation Reactor (KNGR) on the operator mental workload. Empirical experiments were conducted to measure the operator mental workloads of KNGR and Yong-Gwang Unit 3 and 4, respectively. A comparison analysis based on a NASA TLX revealed that Yong-Gwang Unit 3 and 4 were superior to KNGR in terms of the mental workload. Post-hoc analyses showed that the mental workload of senior reactor operators was significantly higher than those of reactor and turbine operators, regardless of plant types. The implications of the findings were discussed in detail.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.25 no.4
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• pp.71-78
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• 2011

This paper contains the selection of operation parameters for protection and control of steam turbine in a Korea Standard Type Nuclear Power Plant. The safety of nuclear reactor must be ensured which generates nuclear energy and produces steam. Also, the safety of turbine, which consume the nuclear energy as a core machine, must be ensured. For the purpose of this, we describe how the operating parameters were selected, reviewed, implemented into the operator console and finally put into actual operation of the system.

• International Journal of Safety
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• v.11 no.1
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• pp.26-32
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• 2012

This paper introduces a feasibility evaluation method for prognosis systems based on an empirical model in nuclear power plants. By exploiting the dynamical signature characterized by abnormal phenomena, the prognosis technique can be applied to detect the plant abnormal states prior to an unexpected plant trip. Early $operator^{\circ}{\emptyset}s$ awareness can extend available time for operation action; therefore, unexpected plant trip and time-consuming maintenance can be reduced. For the practical application in nuclear power plant, it is important not only to enhance the advantages of prognosis systems, but also to quantify the negative impact in prognosis, e.g., uncertainty. In order to apply these prognosis systems to real nuclear power plants, it is necessary to conduct a feasibility evaluation; the evaluation consists of 4 steps (: the development of an evaluation method, the development of selection criteria for the abnormal state, acquisition and signal processing, and an evaluation experiment). In this paper, we introduce the feasibility evaluation method and propose further study points for applying prognosis systems from KHNP's experiences in testing some prognosis technologies available in the market.

• 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.28 no.6
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• pp.522-531
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• 1996

The adoption of expert systems mainly as operator supporting systems is becoming increasingly popular as the control algorithms of system become more and more sophisticated and complicated. The verification phase of knowledge base is an important part for developing reliable expert systems, especially in nuclear industry. Although several strategies or tools have been developed to perform potential error checking, they often neglect the reliability of verification methods. Because a Petri net provides a uniform mathematical formalization of knowledge base, it has been employed for knowledge base verification. In this work, we devise and suggest an automated tool, called COKEP(Checker Of Knowledge base using Extended Petri net), for detecting incorrectness, inconsistency, and incompletensess in a knowledge base. The scope of the verification problem is expanded to chained errors, unlike previous studies that assume error incidence to be limited to rule pairs only. In addition, we consider certainty factor in checking, because most of knowledge bases have certainty factors.

• Nuclear Engineering and Technology
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• v.54 no.4
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• pp.1195-1205
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• 2022

Recent developments on spectral diffusion algorithms, i.e., algorithms which exploit the projection of the solution on the eigenfunctions of the Laplacian operator, demonstrated their effective applicability in fast transient conditions. Nevertheless, the numerical error introduced by these algorithms, together with the uncertainties associated with model parameters, may impact the reliability of the predictions on short-lived volatile fission product release from nuclear fuel. In this work, we provide an upper bound on the numerical error introduced by the presented spectral diffusion algorithm, in both constant and time-varying conditions, depending on the number of modes and on the time discretization. The definition of this upper bound allows introducing a methodology to a priori bound the numerical error on short-lived volatile fission product retention.