• 한국가스학회지
• /
• 제14권5호
• /
• pp.38-44
• /
• 2010

본 논문은 철도를 통해 운송되는 프로필렌의 사고위험을 정량적으로 분석하였다. 프로필렌의 수송 경로에 따라 사고 시 피해 위험이 높을 것으로 예상되는 지역인 익산역, 순천역, 전주역으로 대상지역을 선정하였다. 프로필렌의 운송 중 일어날 수 있는 사고유형을 고려한 후 ETA(Event Tree Analysis)를 이용하여 사고시나리오 및 발생빈도를 도출하였고, PHAST 6.53(Process Hazard Analysis Software Tool)을 이용하여 사고피해예측 평가 실시하여 주변에 미치는 피해정도를 산정함으로써 개인적.사회적 위험성정도를 제시하였다.

• 한국안전학회지
• /
• 제35권4호
• /
• pp.48-55
• /
• 2020

The use of temporary Gondola has been steadily increasing. The temporary Gondola is required to get a safety certification review during installation and to be inspected during use within every six months. Most of them, however, are dismantled before six months, and inappropriate activities are conducted frequently for shorter working hours and convenience of work. In this study, the characteristics of the temporary Gondola and the domestic accident cases that occurred over the past 10 years(2008-2017) are analyzed for the type of accident, the state of the accident by year, and the actions of the workers in the event of an accident. Also comprehensive accident reduction measures were proposed by identifying the fundamental causes of temporary Gondola accidents, problems of existing preventive measures, and system defects by utilizing Bow-Tie techniques.

• Safety and Health at Work
• /
• 제8권3호
• /
• pp.306-314
• /
• 2017

Background: In order to obtain a deeper understanding of an incident, it needs to be investigated to "peel back the layers" and examine both immediate and underlying failures that contributed to the event itself. One of the key elements of an effective accident investigation is recording the scene for future reference. In recent years, however, there have been major advances in survey technology, which have provided the ability to capture scenes in three dimension to an unprecedented level of detail, using laser scanners. Methods: A case study involving a fatal incident was surveyed using three-dimensional laser scanning, and subsequently recreated through virtual and physical models. The created models were then utilized in both accident investigation and legal process, to explore the technologies used in this setting. Results: Benefits include explanation of the event and environment, incident reconstruction, preservation of evidence, reducing the need for site visits, and testing of theories. Drawbacks include limited technology within courtrooms, confusion caused by models, cost, and personal interpretation and acceptance in the data. Conclusion: Laser scanning surveys can be of considerable use in jury trials, for example, in case the location supports the use of a high-definition survey, or an object has to be altered after the accident and it has a specific influence on the case and needs to be recorded. However, consideration has to be made in its application and to ensure a fair trial, with emphasis being placed on the facts of the case and personal interpretation controlled.

• 한국가스학회지
• /
• 제15권2호
• /
• pp.33-39
• /
• 2011

이 논문은 철도를 이용한 폭약류의 운송 시 사고위험을 정량적으로 제시하였다. 사고유형은 역내에서의 사고와 수송 중의 사고로 분류하였다. 그리고 각각의 유형에 따라 열차의 탈선사고와 충돌사고의 빈도를 통해 사고빈도의 초기 값을 제시하였으며 ETA(Event Tree Analysis)를 통하여 사고빈도의 결과를 도출하였다. 피해영향평가는 TNT Equivalent method과 Probit analysis method를 이용하였다. 리스크 평가 결과 인구밀도가 높은 지역을 통과하는 폭약류의 철도운송은 사고발생시 높은 인명피해를 야기 시킬 수 있는 것으로 나타났다. 특히 유류와 복합된 사고의 경우 대형 폭발사고로 이어질 리스크를 가진 것으로 예측되었다. 결론적으로 폭약류의 위험물 수송 시 인구밀도가 높아 피해영향이 높은 지역의 경유를 줄이고 또한 리스크를 경감시킬 수 있는 대책을 강구해 위험요소와 사고빈도를 줄 일 필요성이 있을 것이다.

• 디지털융복합연구
• /
• 제10권5호
• /
• pp.223-232
• /
• 2012

최근 개인정보에 대한 유출과 침해행위가 급증하면서 악의적인 목적의 피해사례가 급증하고 있다. 대부분의 사용자가 윈도우즈 운영체제를 사용하고 있으며, 최근 Windows 7 운영체제가 발표되면서 Windows 7 OS 환경에서의 침해대응 기법에 대한 연구가 필요하다. 현재까지 개발된 침해사고 대응 기법은 대부분 Windows XP 또는 Windows Vista를 중심으로 구현되어 있다. 윈도우즈 운영체제에서 시스템 침해사고를 효율적으로 분석하기 위해서는 시스템에서 생성되는 이벤트 정보의 시간정보 및 보안 위협 가중치 정보를 중심으로 이를 시각적으로 분석할 필요가 있다. 따라서 본 논문에서는 최근 발표된 Windows 7 운영체제에서 생성되는 시스템 이벤트 정보에 대해 시각적으로 분석하고 이를 통해 시스템 침해사고를 분석할 수 있는 시스템을 설계 및 구현하였다. 본 논문에서 개발된 시스템을 이용할 경우 보다 효율적인 침해사고 분석이 가능할 것으로 예상된다.

• 한국방재안전학회논문집
• /
• 제11권2호
• /
• pp.45-52
• /
• 2018

본 연구는 2017년 8월 17일 청계천에서 발생한 시민고립사고의 원인을 규명하고, 고밀도 기상관측망의 관측자료를 이용하여 안전한 도시하천 관리 방안을 제시한 연구이다. SK 텔레콤 기지국에 설치된 고밀도 기상관측망인 SK techx와 상대적으로 공간적 밀도가 낮은 기상청 AWS의 사고 당일 강우자료를 도시유출모형에 적용하여 당시 상황을 모의하였다. 사고원인 중 하나로 가정한 CSO 관로 내 체수현상을 구현하여 수치모의한 결과, 기상청 AWS에서 계측된 강우량은 사고를 발생시키지 않았다. 하지만 실제 현상과 더 유사한 고밀도 기상관측망인 SK techx의 강우자료를 적용했을 때는 당일 발생한 사고와 유사한 결과가 나타났다. 이는 낮은 공간 밀도인 기상청 AWS는 청계천에서 일어나는 실제현상을 예측할 수 없고, 안전한 하천관리르 위해 고밀도 기상관측소가 필요하다는 것을 의미한다. 또한 CSO 관로 내 체수 유무를 독립변수로 수치 모의한 결과 비우당교의 CSO 관로 내 체수가 사고의 직접적인 원인으로 분석되었다.

• 국제학술발표논문집
• /
• The 9th International Conference on Construction Engineering and Project Management
• /
• pp.744-751
• /
• 2022

Construction is among the most dangerous industries with numerous accidents occurring at job sites. Following an accident, an investigation report is issued, containing all of the specifics. Analyzing the text information in construction accident reports can help enhance our understanding of historical data and be utilized for accident prevention. However, the conventional method requires a significant amount of time and effort to read and identify crucial information. The previous studies primarily focused on analyzing related objects and causes of accidents rather than the construction activities. This study aims to extract construction activities taken by workers associated with accidents by presenting an automated framework that adopts a deep learning-based approach and natural language processing (NLP) techniques to automatically classify sentences obtained from previous construction accident reports into predefined categories, namely TRADE (i.e., a construction activity before an accident), EVENT (i.e., an accident), and CONSEQUENCE (i.e., the outcome of an accident). The classification model was developed using Convolutional Neural Network (CNN) showed a robust accuracy of 88.7%, indicating that the proposed model is capable of investigating the occurrence of accidents with minimal manual involvement and sophisticated engineering. Also, this study is expected to support safety assessments and build risk management systems.

• Nuclear Engineering and Technology
• /
• 제44권4호
• /
• pp.393-404
• /
• 2012

After the Fukushima nuclear accident in 2011, there has been increasing concern regarding severe accidents in nuclear facilities. Severe accident scenarios are difficult for operators to monitor and identify. Therefore, accurate prediction of a severe accident is important in order to manage it appropriately in the unfavorable conditions. In this study, artificial intelligence (AI) techniques, such as support vector classification (SVC), probabilistic neural network (PNN), group method of data handling (GMDH), and fuzzy neural network (FNN), were used to monitor the major transient scenarios of a severe accident caused by three different initiating events, the hot-leg loss of coolant accident (LOCA), the cold-leg LOCA, and the steam generator tube rupture in pressurized water reactors (PWRs). The SVC and PNN models were used for the event classification. The GMDH and FNN models were employed to accurately predict the important timing representing severe accident scenarios. In addition, in order to verify the proposed algorithm, data from a number of numerical simulations were required in order to train the AI techniques due to the shortage of real LOCA data. The data was acquired by performing simulations using the MAAP4 code. The prediction accuracy of the three types of initiating events was sufficiently high to predict severe accident scenarios. Therefore, the AI techniques can be applied successfully in the identification and monitoring of severe accident scenarios in real PWRs.

• 전기학회논문지
• /
• 제59권1호
• /
• pp.9-15
• /
• 2010

As catenary supply electric power directly to the railway system, it is very important to prevent an accident of a catenary for appropriate train operation. This paper proposed the assessment the outage data for "British Catenary Safety Analysis Report" and Korean data to compare the reliability of the railway system. The analyzed data were applied to Event Tree and Fault Tree algorithm to calculate the reliability indices of railway system. Event tree is created and gate results of fault tree analysis are used as the source of event tree probabilities. Fault tree represents the interaction of failures and basic events within a system. Event Tree and Fault Tree analysis result is helpful to assess the reliability to interpreted. The reliability indices can be used to determine the equipment to be replaced for the entire system reliability improvement.

• Radiation Oncology Journal
• /
• 제31권2호
• /
• pp.88-96
• /
• 2013

Purpose: This study identifies accident sequences from the past accidents in order to help the risk analysis application to the external radiotherapy. Materials and Methods: This study reviews 59 accidental cases in two retrospective safety analyses that have collected the incidents in the external radiotherapy extensively. Two accident analysis reports that accumulated past incidents are investigated to identify accident sequences including initiating events, failure of safety measures, and consequences. This study classifies the accidents by the treatments stages and sources of errors for initiating events, types of failures in the safety measures, and types of undesirable consequences and the number of affected patients. Then, the accident sequences are grouped into several categories on the basis of similarity of progression. As a result, these cases can be categorized into 14 groups of accident sequence. Results: The result indicates that risk analysis needs to pay attention to not only the planning stage, but also the calibration stage that is committed prior to the main treatment process. It also shows that human error is the largest contributor to initiating events as well as to the failure of safety measures. This study also illustrates an event tree analysis for an accident sequence initiated in the calibration. Conclusion: This study is expected to provide sights into the accident sequences for the prospective risk analysis through the review of experiences.