• Nuclear Engineering and Technology
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• v.54 no.3
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• pp.896-908
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• 2022

As a part of probabilistic risk (or safety) assessment (PRA or PSA) of nuclear power plants (NPPs), the primary role of human reliability analysis (HRA) is to provide credible estimations of the human error probabilities (HEPs) of safety-critical tasks. In this regard, it is vital to provide credible HEPs based on firm technical underpinnings including (but not limited to): (1) how to collect HRA data from available sources of information, and (2) how to inform HRA practitioners with the collected HRA data. Because of these necessities, the U.S. Nuclear Regulatory Commission and the Korea Atomic Energy Research Institute independently developed two dedicated HRA data collection systems, SACADA (Scenario Authoring, Characterization, And Debriefing Application) and HuREX (Human Reliability data EXtraction), respectively. These systems provide unique frameworks that can be used to secure HRA data from full-scope training simulators of NPPs (i.e., simulator data). In order to investigate the applicability of these two systems, two papers have been prepared with distinct purposes. The first paper, entitled "SACADA and HuREX: Part 1. The Use of SACADA and HuREX Systems to Collect Human Reliability Data", deals with technical issues pertaining to the collection of HRA data. This second paper explains how the two systems are able to inform HRA practitioners. To this end, the process of estimating HEPs is demonstrated based on feed-and-bleed operations using HRA data from the two systems.

• Journal of Korea Entertainment Industry Association
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• v.5 no.1
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• pp.122-126
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• 2011

In this paper, for the purpose of improving the future domestic train control systems and securing interoperability according to the global development trends of train control systems, we present the test results of interoperability between wayside train control system installed in existed line, and the onboard train control system. Due to the safety-critical characteristics of train systems, the site test in the section where the wayside equipment is installed, leads to a danger against safety. Therefore, by way of constructing a simulation environment of train control systems, we confirm the T/R data systems of the equipment for interoperability and test the interoperability by applying these systems to onboard equipment.

• Journal of the Korean Society of Systems Engineering
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• v.14 no.2
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• pp.24-32
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• 2018

System Complexity one of the most common cause failure of the projects, it leads to a lack of understanding about the functions of the system. Hence, the model is developed for communication and furthermore modeling help analysis, design, and understanding of the system. On the other hand, the text-based specification is useful and easy to develop but is difficult to visualize the physical composition, structure, and behaviour or data exchange of the system. Therefore, it is necessary to transform system description into a diagram which clearly depicts the behaviour of the system as well as the interaction between components. According to the International Atomic Energy Agency (IAEA) Safety Glossary, The safety system is a system important to safety, provided to ensure the safe shutdown of the reactor or the residual heat removal from the reactor core, or to limit the consequences of anticipated operational occurrences and design basis accidents. Core Protection Calculator System (CPCS) in Advanced Power Reactor 1400 (APR 1400) Nuclear Power Plant is a safety critical system. CPCS was developed using systems engineering method focusing on Departure from Nuclear Boiling Ratio (DNBR) calculation. Due to the complexity of the system, many diagrams are needed to minimize the risk of ambiguities and lack of understanding. Using Model-Based Systems Engineering (MBSE) software for modeling the DNBR algorithm were used. These diagrams then serve as the baseline of the reverse engineering process and speeding up the development process. In addition, the use of MBSE ensures that any additional information obtained from auxiliary sources can then be input into the system model, ensuring data consistency.

• Journal of East-West Nursing Research
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• v.19 no.1
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• pp.46-54
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• 2013

Purpose: An objective of this study was to investigate nurses' perceptions toward patient safety culture and to examine the factors affecting safety care activities. Methods: The participants were 429 nurses, at 6 hospitals located in regions, which have 150 to 300 beds, and HSOPSC (AHRQ, 2009) and questionnaire on safety care activities were used as measurement tools. Descriptive statistics, independent t-test, one way ANOVA, and stepwise multiple regression with SPSS/WIN version12.0 were used to analyze the data. Results: Supervisor manager expectations and actions promoting patients safety and frequency of events reported were the highest as positive responses, whereas staffing and nonpunitive response to errors showed the lowest scores as positive responses. Scores of medication surveillance is the highest while firefighting surveillance is the lowest in terms of safety care activities. Significant predictors influencing safety care activities were frequency of events report, handoffs and transitions, work unit a patient safety grade, organizational learning-continuous improvement, and teamwork across units. These predictors account for 23% of the variance. Conclusion: These results suggest that hospital policies and systems should be built to settle patient safety culture effectively. Development of standard manuals for safety care activities is another critical element for promoting patient safety.

• Nuclear Engineering and Technology
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• v.40 no.5
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• pp.365-374
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• 2008

Dependability-critical systems, such as digital instrumentation and control systems in nuclear power plants, necessitate engineering techniques and tools to provide assurances of their safety and reliability. Determining system reliability at the architectural design phase is important since it may guide design decisions and provide crucial information for trade-off analysis and estimating system cost. Despite this, reliability and system engineering remain separate disciplines and engineering processes by which the dependability analysis results may not represent the designed system. In this article we provide an overview and application of our approach to build architecture-based, dynamic system models for dependability-critical systems and then automatically generate dynamic fault trees (DFT) for comprehensive, tool-supported reliability analysis. Specifically, we use the Architectural Analysis and Design Language (AADL) to model the structural, behavioral and failure aspects of the system in a composite architecture model. From the AADL model, we seek to derive the DFT(s) and use Galileo's automated reliability analyses to estimate system reliability. This approach alleviates the dependability engineering - systems engineering knowledge expertise gap, integrates the dependability and system engineering design and development processes and enables a more formal, automated and consistent DFT construction. We illustrate this work using an example based on a dynamic digital feed-water control system for a nuclear reactor.

• Nuclear Engineering and Technology
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• v.51 no.7
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• pp.1791-1798
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• 2019

Instrumentation and Control (I&C) systems of nuclear power plants (NPPs) have been continuously digitalized. These systems have a critical role in the operation of nuclear facilities by functioning as the brain of NPPs. In recent years, as cyber security threats to NPP systems have increased, regulatory and policy-related organizations around the world, including the International Atomic Energy Agency (IAEA), Nuclear Regulatory Commission (NRC) and Korea Institute of Nuclear Nonproliferation and Control (KINAC), have emphasized the importance of nuclear cyber security by publishing cyber security guidelines and recommending cyber security requirements for NPP facilities. As described in NRC Regulatory Guide (Reg) 5.71 and KINAC RS015, challenge response authentication should be applied to the critical digital I&C system of NPPs to satisfy the cyber security requirements. There have been no cases in which the most robust response authentication technology like challenge response has been developed and applied to nuclear I&C systems. This paper presents a challenge response authentication mechanism for a Programmable Logic Controller (PLC) system used as a control system in the safety system of the Advanced Power Reactor (APR) 1400 NPP.

• Nuclear Engineering and Technology
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• v.40 no.5
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• pp.397-408
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• 2008

This paper describes the application of a software fault tree analysis (FTA) as one of the analysis techniques for a software safety analysis (SSA) at the design phase and its analysis results for the safety-critical software of a digital reactor protection system, which is called the KNICS RPS, being developed in the KNICS (Korea Nuclear Instrumentation & Control Systems) project. The software modules in the design description were represented by function blocks (FBs), and the software FTA was performed based on the well-defined fault tree templates for the FBs. The SSA, which is part of the verification and validation (V&V) activities, was activated at each phase of the software lifecycle for the KNICS RPS. At the design phase, the software HAZOP (Hazard and Operability) and the software FTA were employed in the SSA in such a way that the software HAZOP was performed first and then the software FTA was applied. The software FTA was applied to some critical modules selected from the software HAZOP analysis.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.29 no.2
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• pp.365-375
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• 2019

A PLC (Programmable Logic Controller) is a highly-reliable industrial digital computer which supports real-time embedded control applications for safety-critical control systems. Real-time operating systems such as uC/OS have been used for PLCs and must meet real-time constraints. As PLCs have been widely used for industrial control systems and connected to the Internet, they have been becoming a main target of cyberattacks. In this paper, we propose an execution code sanitizer to enhance the security of PLC systems. The proposed sanitizer analyzes PLC programs developed by an IDE before downloading the program to a target PLC, and mitigates security vulnerabilities of the program. Our sanitizer can detect vulnerable function calls and illegal memory accesses in development of PLC programs using a database of vulnerable functions as well as the other database of code patterns related to pointer misuses. Based on these DBs, it detects and removes abnormal use patterns of pointer variables and existence of vulnerable functions shown in the call graph of the target executable code. We have implemented the proposed technique and verified its effectiveness through experiments.

• Proceedings of the SAREK Conference
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• 2008.06a
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• pp.90-95
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• 2008

This article presents practical advice regarding the implementation and management of an impeccable Building Management System. The BMS was introduced to the series of computerized systems including manufacturing, storage, distribution, and quality control. Recently revised GMP regulation is requesting an improvement in drug product quality regulatory system by computer system validation. Quality is critical to guarantee the efficacy and the safety of drugs and is approved in the evaluation process after the audit trail application. HVAC parameter monitoring system will record the identity of operators entering or confirming critical data. Authority to amend entered data should be restricted to nominated persons. Any alteration to an entry of critical data should be authorized in advance and recorded with the reason for the change.

• Journal of the Korean Society of Systems Engineering
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• v.16 no.2
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• pp.38-46
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• 2020

The accurate measurement of critical heat flux (CHF) in flow boiling is important for the safety requirement of the nuclear power plant to prevent sharp degradation of the convective heat transfer between the surface of the fuel rod cladding and the reactor coolant. In this paper, a System Engineering approach is used to develop a model that predicts the CHF using machine learning. The model is built using artificial neural network (ANN). The model is then trained, tested and validated using pre-existing database for different flow conditions. The Talos library is used to tune the model by optimizing the hyper parameters and selecting the best network architecture. Once developed, the ANN model can predict the CHF based solely on a set of input parameters (pressure, mass flux, quality and hydraulic diameter) without resorting to any physics-based model. It is intended to use the developed model to predict the DNBR under a large break loss of coolant accident (LBLOCA) in APR1400. The System Engineering approach proved very helpful in facilitating the planning and management of the current work both efficiently and effectively.