• Title/Summary/Keyword: accident analysis model

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A Study on the Analysis of Application of Non-metric Camera to Accident Sites (비측량용 사진기를 이용한 사고현장 적용 해석에 관한 연구)

  • Yeu, Bock Mo;Kim, In Sup;Cho, Gi Sung
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.11 no.4
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    • pp.121-131
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    • 1991
  • This study is about the analysis of the application of non-metric camera to accident sites and aims to present an efficient, an economical and an accurate method of processing accident sites. This was accomplished by observation and accuracy analysis of an experimental model. It can be concluded that by applying the 3-D coordinate system and the bundle adjustment with additional parameters to non-metric cameras, it is possible to achieve an accuracy level of positional values which is similar to that achieved by conventional control surveying and by metric cameras. It was also found that the accuracy of absolute coordinates approached towards the accuracy of metric cameras with the increase of the film size and with the increase of the focal length of the non-metric camera.

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Statistical Analysis of Major Accident Reports and Development of a Real-time Detection Model for Portable Ladder and Safety Helmet (이동식사다리 중대재해 통계 분석 및 이동식사다리와 안전모 실시간 탐지 기계학습 모델 개발)

  • Choi, Seung-Ju;Jung, Kihyo
    • Journal of the Korea Safety Management & Science
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    • v.23 no.1
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    • pp.9-15
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    • 2021
  • The leading source of occupational fatalities is a portable ladder in Korea because it is widely used in industry as work platform. In order to reduce victims, it is necessary to establish preventive measures for the accidents caused by portable ladder. Therefore, this study statistically analyzed injury death by portable ladder for recent 10 years to investigate the accident characteristics. Next, to monitor wearing of safety helmet in real-time while working on a portable ladder, this study developed an object detection model based on the You Only Look Once(YOLO) architecture, which can accurately detect objects within a reasonable time. The model was trained on 6,023 images with/without ladders and safety helmets. The performance of the proposed detection model was 0.795 for F1 score and 0.843 for mean average precision. In addition, the proposed model processed at least 25 frames per second which make the model suitable for real-time application.

Development of a Fission Product Transport Module Predicting the Behavior of Radiological Materials during Severe Accidents in a Nuclear Power Plant

  • Kang, Hyung Seok;Rhee, Bo Wook;Kim, Dong Ha
    • Journal of Radiation Protection and Research
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    • v.41 no.3
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    • pp.237-244
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    • 2016
  • Background: Korea Atomic Energy Research Institute is developing a fission product transport module for predicting the behavior of radioactive materials in the primary cooling system of a nuclear power plant as a separate module, which will be connected to a severe accident analysis code, Core Meltdown Progression Accident Simulation Software (COMPASS). Materials and Methods: This fission product transport (COMPASS-FP) module consists of a fission product release model, an aerosol generation model, and an aerosol transport model. In the fission product release model there are three submodels based on empirical correlations, and they are used to simulate the fission product gases release from the reactor core. In the aerosol generation model, the mass conservation law and Raoult's law are applied to the mixture of vapors and droplets of the fission products in a specified control volume to find the generation of the aerosol droplet. In the aerosol transport model, empirical correlations available from the open literature are used to simulate the aerosol removal processes owing to the gravitational settling, inertia impaction, diffusiophoresis, and thermophoresis. Results and Discussion: The COMPASS-FP module was validated against Aerosol Behavior Code Validation and Evaluation (ABCOVE-5) test performed by Hanford Engineering Development Laboratory for comparing the prediction and test data. The comparison results assuming a non-spherical aerosol shape for the suspended aerosol mass concentration showed a good agreement with an error range of about ${\pm}6%$. Conclusion: It was found that the COMPASS-FP module produced the reasonable results of the fission product gases release, the aerosol generation, and the gravitational settling in the aerosol removal processes for ABCOVE-5. However, more validation for other aerosol removal models needs to be performed.

Integrated Level 1-Level 2 decommissioning probabilistic risk assessment for boiling water reactors

  • Mercurio, Davide;Andersen, Vincent M.;Wagner, Kenneth C.
    • Nuclear Engineering and Technology
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    • v.50 no.5
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    • pp.627-638
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    • 2018
  • This article describes an integrated Level 1-Level 2 probabilistic risk assessment (PRA) methodology to evaluate the radiological risk during postulated accident scenarios initiated during the decommissioning phase of a typical Mark I containment boiling water reactor. The fuel damage scenarios include those initiated while the reactor is permanently shut down, defueled, and the spent fuel is located into the spent fuel storage pool. This article focuses on the integrated Level 1-Level 2 PRA aspects of the analysis, from the beginning of the accident to the radiological release into the environment. The integrated Level 1-Level 2 decommissioning PRA uses event trees and fault trees that assess the accident progression until and after fuel damage. Detailed deterministic severe accident analyses are performed to support the fault tree/event tree development and to provide source term information for the various pieces of the Level 1-Level 2 model. Source terms information is collected from accidents occurring in both the reactor pressure vessel and the spent fuel pool, including simultaneous accidents. The Level 1-Level 2 PRA model evaluates the temporal and physical changes in plant conditions including consideration of major uncertainties. The goal of this article is to provide a methodology framework to perform a decommissioning Probabilistic Risk Assessment (PRA), and an application to a real case study is provided to show the use of the methodology. Results will be derived from the integrated Level 1-Level 2 decommissioning PSA event tree in terms of fuel damage frequency, large release frequency, and large early release frequency, including uncertainties.

Development of Accident Prediction Models for Freeway Interchange Ramps (고속도로 인터체인지 연결로에서의 교통사고 예측모형 개발)

  • Park, Hyo-Sin;Son, Bong-Su;Kim, Hyeong-Jin
    • Journal of Korean Society of Transportation
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    • v.25 no.3
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    • pp.123-135
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    • 2007
  • The objective of this study is to analyze the relationship between traffic accidents occurring at trumpet interchange ramps according to accident type as well as the relevant factors that led to the traffic accidents, such as geometric design elements and traffic volumes. In the process of analysis of the distribution of traffic accidents, negative binomial distribution was selected as the most appropriate model. Negative binomial regression models were developed for total trumpet interchange ramps, direct ramps, loop ramps and semi-direct ramps based on the negative binomial distribution. Based upon several statistical diagnostics of the difference between observed accidents and predicted accidents with four previously developed models, the fit proved to be reasonable. Understanding of statistically significant variables in the developed model will enable designers to increase efficiency in terms of road operations and the development of traffic accident prevention policies in accordance with road design features.

The Effects of Individual Accidents and Neighborhood Environmental Characteristics on the Severity of Pedestrian Traffic Accidents in Seoul (개별 사고특성 및 근린환경 특성이 서울시 보행자 교통사고 심각도에 미치는 영향)

  • Ko, Dong-Won;Park, Seung-Hoon
    • Journal of the Architectural Institute of Korea Planning & Design
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    • v.35 no.8
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    • pp.101-109
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    • 2019
  • Korea's transportation paradigm is shifting from a vehicle-oriented transportation plan to a pedestrian-friendly environment that emphasizes walking safety. However, the level of pedestrian traffic accidents in Korea is still high and serious. The purpose of this study is to investigate factors affecting the severity of pedestrians traffic accidents using the multilevel logistic regression model based on 2015-2017 pedestrian accidents data provided by the Traffic Accident Analysis System(TAAS). The main results of the multilevel logistic regression model showed that 89% of pedestrian traffic accidents in Seoul were explained by individual characteristics such as drivers and pedestrians, and 11% were explained by neighborhood environmental characteristics. The results are as follows : In the individual characteristics such as pedestrians and drivers, the older the pedestrians and the drivers, the higher the traffic accident severity. The severity of traffic accidents was high when the pedestrians were female and the drivers were male. In the case of accident types, traffic accidents were more serious in the cases of heavy vehicles, inclement weather, and occurring at intersections and crosswalks. The results of the neighborhood environmental characteristics are as follows. The intersection density and the crosswalk density tended to reduce the severity of traffic accidents. On the other hand, the traffic light density and the school zones were founded to related to the higher level of traffic accident severity. This study suggests that both individual and neighborhood environmental characteristics should be considered together to prevent and reduce the severity of pedestrian traffic accidents.

Analysis of Crane Accidents by Using a Man-Machine System Model (인간-기계 시스템 모델에 의한 크레인 사망재해 분석)

  • Park, Jae-Hee;Park, Tae-Joo;Lim, Hyun-Kyo;Seo, Eun-Hong
    • Journal of the Korean Society of Safety
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    • v.22 no.2 s.80
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    • pp.59-66
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    • 2007
  • As the need of handling heavy materials increases, various cranes are used in industries. However, the effectiveness of crane also entails industrial accidents such as falling, constriction etc. In fact, the number of fatal accidents caused by crane is still high in Korea. To find out the causes of the accidents in terms of human error, we developed a man-machine system model that consists of two axes; human information processing and crane life cycle. In the human information processing dimension, we simplified it as five functions; sensing and perception, decision making and memory, response etc. In the crane life cycle dimension, we divided it into nine phases; design, production, operation etc. For the 152 fatal accident records during 1999-2006 years, we classified them into 45 cells made by two axes. Then we identified the preceding causes of the classified crane accident based on performance shaping factors. As the results of statistical analysis, the overall trend of crane fatal accidents was described. For the cause analysis, wrong decision making in work plan phase shows the highest frequency. Next, the poor information input in crane operation followed in accident frequency. In ergonomics view, the problems of interface design in displays and controls made 11.8% of fatal accidents. Following the analysis, several ergonomic design guidelines to prevent crane accidents were suggested.

A Method to Measure Damage Areas by the types of Railroad Hazardous Material through GIS Spatial Analysis (GIS 공간 분석기법을 통한 철도사고위험물질별 피해규모 자동추출방안)

  • Kim, Sang-Gyun;Kim, Si-Gon;Lee, Won-Tea
    • Proceedings of the KSR Conference
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    • 2009.05a
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    • pp.1769-1778
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    • 2009
  • Due to the industrialization and urbanization, the transport of hazardous materials increases, which rises possibilities in occurring prospective accidents in terms of hazardous material transport as well. This study applied the model developed from the previous research to analyze the scale of damage areas from the accidents related to hazardous material accidents, as well as suggested a method to measure automatically the scale of accident including casualties and environmental damage based on the guideline which suggests the quantities of hazardous materials exposed from an accident and was defined in the study of standardization for hazardous material classification. A buffering analysis technique of Geographic Information System (GIS) was applied for that. To apply the model which evaluates the scale of population and exposure to environment on each link, rail network, zones, rail accident data, rail freight trips, and locations of rivers etc were complied as a database for GIS analysis. In conclusion, a method to measure damage areas by the types of hazardous materials was introduced using a Clip and a Special Join technique for overlay analysis.

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Analysis-based Pedestrian Traffic Incident Analysis Based on Logistic Regression (로지스틱 회귀분석 기반 노인 보행자 교통사고 요인 분석)

  • Siwon Kim;Jeongwon Gil;Jaekyung Kwon;Jae seong Hwang;Choul ki Lee
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.23 no.2
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    • pp.15-31
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    • 2024
  • The characteristics of elderly traffic accidents were identified by reflecting the situation of the elderly population in Korea, which is entering an ultra-aging society, and the relationship between independent and dependent variables was analyzed by classifying traffic accidents of serious or higher and traffic accidents of minor or lower in elderly pedestrian traffic accidents using binomial variables. Data collection, processing, and variable selection were performed by acquiring data from the elderly pedestrian traffic accident analysis system (TAAS) for the past 10 years (from 13 to 22 years), and basic statistics and analysis by accident factors were performed. A total of 15 influencing variables were derived by applying the logistic regression model, and the influencing variables that have the greatest influence on the probability of a traffic accident involving severe or higher elderly pedestrians were derived. After that, statistical tests were performed to analyze the suitability of the logistic model, and a method for predicting the probability of a traffic accident according to the construction of a prediction model was presented.

Analysis of Elderly Drivers' Accident Models Considering Operations and Physical Characteristics (고령운전자 운전 및 신체특성을 반영한 교통사고 분석 연구)

  • Lim, Sam Jin;Park, Jun Tae;Kim, Young Il;Kim, Tae Ho
    • Journal of Korean Society of Transportation
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    • v.30 no.6
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    • pp.37-46
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    • 2012
  • The number of traffic accidents caused by elderly drivers over the age of 65 has surged over the past ten years from 37,000 to 274,000 cases. The proportion of elderly drivers' accidents has jumped 3.1 times from 1.2% to 3.7% out of all traffic accidents, and traffic safety organizations are pursuing diverse measures to address the situation. Above all, connecting safety measures with an in-depth research on behavioral and physical characteristics of elderly drivers will prove vital. This study conducted an empirical research linking the driving characteristics and traffic accidents by elderly drivers based on the Driving Aptitude Test items and traffic accident data, which enabled the measurement of behavioral characteristics of elderly drivers. In developing the Influence Model, we applied the zero-inflated Poisson (ZIP) regression model and selected an accident prediction model based on the Bayesian Influence in regards to the ZIP regression model and the zero-inflated negative binomial (ZINB) regression model. According to the results of the AAE analysis, the ZIP regression model was more appropriate and it was found that three variables? prediction of velocity, diversion, and cognitive ability? had a relation of influence with traffic accidents caused by elderly drivers.