• 한국철도학회논문집
• /
• 제11권4호
• /
• pp.404-409
• /
• 2008

본 논문은 크게 두 가지 내용을 담고 있다. 하나는 기 개발된 철도 인간신뢰도분석 방법(R-HRA)의 개정에 관한 내용이며, 다른 하나는 개정된 R-HRA 방법에 기반한 R-HRA 지원 시스템의 개발이다. 개정된 R-HRA 방법은 분석자간 일관성을 유지하기 위한 직무분석 지침의 제공과 영향인자의 분류에 특징을 두고 있으며, R-HRA 지원 시스템은 인간신뢰도분석을 위한 정보의 수집, 내 외적 오류유형을 포함한 정성적 오류분석, 오류확률의 정량화, 전체 분석결과의 문서화 작업 등을 지원하고 있다. 개정된 R-HRA 방법과 지원 소프트웨어는 철도 사고 시나리오에서 발생 가능한 인적오류 가능성을 효과적이고 효율적으로 분석할 수 있도록 지원할 수 있을 것으로 기대된다.

• Nuclear Engineering and Technology
• /
• 제51권5호
• /
• pp.1297-1306
• /
• 2019

Probabilistic safety assessments (PSA) have been used for several decades to visualize the risk level of commercial nuclear power plants (NPPs). Since the role of a human reliability analysis (HRA) is to provide human error probabilities for safety critical tasks to support PSA, PSA quality is strongly affected by HRA quality. Therefore, it is important to understand the underlying limitations or problems of HRA techniques. For this reason, this study conducted a survey among 14 subject matter experts who represent the HRA community of domestic Korean NPPs. As a result, five significant HRA issues were identified: (1) providing a technical basis for the K-HRA (Korean HRA) method, and developing dedicated HRA methods applicable to (2) diverse external events to support Level 1 PSA, (3) digital environments, (4) mobile equipment, and (5) severe accident management guideline tasks to support Level 2 PSA. In addition, an HRA method to support multi-unit PSA was emphasized because it plays an important role in the evaluation of site risk, which is one of the hottest current issues. It is believed that creating such a catalog of prioritized issues will be a good indication of research direction to improve HRA and therefore PSA quality.

• 한국안전학회지
• /
• 제14권2호
• /
• pp.178-191
• /
• 1999

More than twenty methods were suggested for Human Reliability Analysis (HRA) in the field of safety analysis for Nuclear Power Plants (NPPs). However, there is still a high uncertainty on the analysis and a difficulty in performing HRA. New methods and approaches are under studying to overcome such limitations of current HRA. This paper presents some results of study to analysis limitations of current HRA in viewpoint of user, i.e., HRA analyst. The limitation analysis was based on 89 human error events modeled in a Probabilistic Safety Assessment (PSA) project for NPPs in Korea. Total 17 specific limitations were identified and categorized into seven groups. Important analysis has also been undertaken to assess the order of priority among those limitations. Finally, seven requirements with priority ranking were generated for an advanced framework and methodology of HRA.

• Nuclear Engineering and Technology
• /
• 제54권3호
• /
• pp.896-908
• /
• 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.

• Nuclear Engineering and Technology
• /
• 제54권5호
• /
• pp.1686-1697
• /
• 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. Accordingly, HRA community has emphasized the accumulation of HRA data to support HRA practitioners for many decades. To this end, it is critical to resolve practical problems including (but not limited to): (1) how to collect HRA data from available information sources, and (2) how to inform HRA practitioners with the collected HRA data. In this regard, the U.S. Nuclear Regulatory Commission (NRC) and Korea Atomic Energy Research Institute (KAERI) independently initiated two large projects to accumulate HRA data by using full-scale simulators (i.e., simulator data). In terms of resolving the first practical problem, the NRC and KAERI developed two dedicated HRA data collection systems, SACADA (Scenario Authoring, Characterization, And Debriefing Application) and HuREX (Human Reliability data EXtraction), respectively. In addition, to inform HRA practitioners, the NRC and KAERI proposed several ideas to extract useful information from simulator data. This paper is the first of two papers to discuss the technical underpinnings of the development of the SACADA and HuREX systems.

• Nuclear Engineering and Technology
• /
• 제53권2호
• /
• pp.376-385
• /
• 2021

Probabilistic risk assessment (PRA) has improved its elemental technologies used for assessing external events since the Fukushima Daiichi Nuclear Power Station Accident in 2011. HRA needs to be improved for analyzing tasks performed under extreme conditions (e.g., different actors responding to external events or performing operations using portable mitigation equipment). To make these improvements, it is essential to understand plant-specific and scenario-specific conditions that affect human performance. The Nuclear Risk Research Center (NRRC) of the Central Research Institute of Electric Power Industry (CRIEPI) has developed an HRA guide that compiles qualitative analysis methods for collecting plant-specific and scenario-specific conditions that affect human performance into "narratives," reflecting the latest research trends, and models for analysis of tasks under extreme conditions.

• Nuclear Engineering and Technology
• /
• 제54권3호
• /
• pp.948-958
• /
• 2022

Since reliability and security of man-machine system increasingly depend on reliability of human, human reliability analysis (HRA) has attracted a lot of attention in many fields especially in nuclear engineering. Dependence assessment among human tasks is a important part in HRA which contributes to an appropriate evaluation result. Most of methods in HRA are based on experts' opinions which are subjective and uncertain. Also, the dependence influencing factors are usually considered to be constant, which is unrealistic. In this paper, a new model based on Dempster-Shafer evidence theory (DSET) and fuzzy number is proposed to handle the dependence between two tasks in HRA under uncertain and dynamic situations. First, the dependence influencing factors are identified and the judgments on the factors are represented as basic belief assignments (BBAs). Second, the BBAs of the factors that varying with time are reconstructed based on the correction BBA derived from time value. Then, BBAs of all factors are combined to gain the fused BBA. Finally, conditional human error probability (CHEP) is derived based on the fused BBA. The proposed method can deal with uncertainties in the judgments and dynamics of the dependence influencing factors. A case study is illustrated to show the effectiveness and the flexibility of the proposed method.

• 한국안전학회지
• /
• 제18권2호
• /
• pp.98-103
• /
• 2003

Based on ASME probabilistic risk assessment (PRA) and NEI PRA peer review guidance, we evaluate a human reliability analysis (HRA) in probabilistic safety assessment (PSA) for Korea standard nuclear power plants, Ulchin Unit 3&4, to improve it performed at under design. The HRA for Ulchin Unit 3&4 is assessed as higher than Grade I based on ASME PRA standard and as higher than Grade 2 based on NEI PRA peer review guidance. The major items to be improved identified through the evaluation process are the documentation, the systematic human reliability analysis, the participitation of operators in the works and review of HRA. We suggest the guidance on the identification and qualitative screening analysis for pre-accident human errors and solve some items to be improved using the suggested guidance.

• 한국철도학회논문집
• /
• 제9권5호
• /
• pp.532-538
• /
• 2006

The railway human reliability analysis(R-HRA) plays a role of identifying and assessing human failure events in the framework of the probabilistic risk assessment(PRA) of the railway systems. This study introduces a case study that was performed to select an appropriate R-HRA method. Three HRA methods were considered in the case study: (1) the K-MRA(THERP/ASEP-based) method, (2) the HEART method, (3) the RSSB-HRA method. Two case events were selected based on the review of the railway incidents/accidents, which include (1) a real-end collision event, which occurred on the railway between the Gomo and Kyungsan stations in 2003, (2) the signal passed at danger(SPAD) events, which are caused from a variety of factors. The three HRA methods were applied to both case events, and then the strengths and limitations of each method were derived and compared with each other from the viewpoint of the applicability of a HRA method to the railway industry.

• Nuclear Engineering and Technology
• /
• 제53권11호
• /
• pp.3675-3684
• /
• 2021

Human reliability analysis (HRA) is a proactive approach to model and evaluate human systematic errors, and has been extensively applied in various complicated systems. Dependence assessment among human errors plays a key role in the HRA, which relies heavily on the knowledge and experience of experts in real-world cases. Moreover, there are ofthen different types of uncertainty when experts use linguistic labels to evaluate the dependencies between human failure events. In this context, this paper aims to develop a new method based on linguistic hesitant fuzzy sets and the technique for human error rate prediction (THERP) technique to manage the dependence in HRA. This method handles the linguistic assessments given by experts according to the linguistic hesitant fuzzy sets, determines the weights of influential factors by an extended best-worst method, and confirms the degree of dependence between successive actions based on the THERP method. Finally, the effectiveness and practicality of the presented linguistic hesitant fuzzy THERP method are demonstrated through an empirical healthcare dependence analysis.