• Journal of Korean Society of Environmental Engineers
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• v.33 no.7
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• pp.544-551
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• 2011

The objective of this study was to analyze VIRULO model, a probabilistic quantitative model, which had been developed by US Environmental Protection Agency. The model could assess the viral attenuation capacity of soil as hydrogeologic barrier using Monte Carlo simulation. The governing equations used in the model were composed of unsaturated flow equations and viral transport equations. Among the model parameters, those related to water flow for 11 soil types were from UNDODA data, and those related to 5 virus species were from the literatures. The model compared the attenuation factor with threshold of attenuation to determine the probability of failure and presented the exceedances and Monte Carlo runs as output. The analysis indicated that among 11 USDA soil types, the viral attenuation capacity of loamy sand and sand were far lower than those of clay and silt soils. Also, there were differences in the attenuation in soil among 5 viruses with poliovirus showing the highest attenuation. The viral attenuation capacity of soil decreased sharply with increasing soil water content and increased nonlinearly with increasing soil barrier length. This study indicates that VIRULO model could be considered as a useful screening tool for viral risk assessment in subsurface environment.

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.1385-1389
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• 2010

수자원 계획에 있어서 강우 또는 홍수빈도분석시 주로 사용되는 확률의 개념은 상대빈도에 대한 극한으로 확률을 정의하는 빈도학파적 확률관점에 속하며, 확률모델에서 미지의 매개변수들은 고정된 상수로 간주된다. 따라서 확률은 객관적이고 매개변수들은 고정된 값을 가지기 때문에 이러한 매개변수들에 대한 확률론적 설명은 매우 어렵다. 본 연구에서는 강우빈도해석에서 확률분포의 매개변수에 대한 불확실성을 정량화하기 위하여 베이지안 MCMC 및 Metropolis-Hastings 알고리즘을 이용한 불확실성 평가모델을 구축하였다. 그리고 베이지안 MCMC 및 Metropolis-Hastings 알고리즘의 적용을 통하여 확률강우량 산정시 확률분포의 매개변수에 대한 통계학적 특성 및 불확실성 구간을 정량화하였으며, 이를 바탕으로 홍수위험평가 및 의사결정과정에서 불확실성 및 위험도를 충분히 설명할 수 있는 프레임워크 구성을 위한 기초를 마련할 수 있었다.

• Proceeding of EDISON Challenge
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• 2015.03a
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• pp.24-31
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• 2015

효소는 생명 현상을 구현하는 단백질 촉매인데 그 동안 효소의 촉매 반응 속도는 Michaelis-Menten(MM) 모델로 대부분 설명되어 왔다. 그러나 MM 모델은 실험으로 측정된 단일 효소 반응시간의 확률분포 모양을 설명할 수 없다. MM 모델에 반응계수의 정적 무질서 개념을 도입한 효소 반응 모델도 기질 농도에 따라 변화하는 효소 반응시간의 통계적 요동을 설명하지 못한다. 우리는 단일 효소 반응시간의 통계적 요동이 기질에 따라 변화하는 양상을 설명하기 위해 효소 반응을 구성하는 개별 화학반응을 단순히 푸아송 과정이 아닌 갱신과정(renewal process)으로 확장한 효소 반응 모델을 제안한다. 우리는 이 단일 효소 반응 모델과 기질에 따른 효소 반응시간 분산 변화 데이터를 비교하여 효소-기질 복합체의 지속시간 분포를 간단한 형태로 얻어내었다. 또한, 이 정보를 토대로 전산모사를 수행하여 효소 반응시간의 확률분포를 얻어내고, 실제 실험 결과 및 기존 이론들과 비교하였다. 뿐만 아니라 단일 효소 반응시간의 확률분포를 연속 시간 임의의 보행자(continuous time random walker)의 대기시간 확률분포(waiting time distribution)로 대응하면, 평균 제곱 변위가 시간에 따라 단순히 증가 하지 않는 고분자의 특이 수송(anomalous diffusion) 현상도 정량적으로 설명할 수 있었다.

• Journal of the Earthquake Engineering Society of Korea
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• v.12 no.3
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• pp.1-10
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• 2008

The seismic performance of a structure designed without consideration of seismic loading can be effectively enhanced through seismic rehabilitation. The appropriate level of rehabilitation should be determined based on the decision criteria that minimize the anticipated earthquake-related losses. To estimate the anticipated losses, seismic risk analysis should be performed considering the probabilistic characteristics of the hazard and the structural damage. This study presents the decision procedure in which the probabilistic seismic demand model is utilized for the effective estimation and minimization of the total seismic losses through seismic rehabilitation. The probability density function and the cumulative distribution function of the structural damage for a specified time period are established in a closed form, and are combined with the loss functions to derive the expected seismic loss. The procedure presented in this study could be effectively used for making decisions on the seismic rehabilitation of structural systems.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.17 no.2
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• pp.263-269
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• 2017

'Goal Model' is core knowledge of 'Autonomic Control System' suggested to minimize human interference in system management. 'Autonomic Control System' performs 'Monitoring-Analysis-Plan-Execution', that is the four step of 'Autonomic Control', based on 'Goal Model'. Therefore, it is necessary to quantify achievement ratio of 'Goal Model' of target system. Thus, this paper present 'Probabilistic Evaluation of Goal Model' for methodology how to quantify achievement ratio of 'Goal Model'. It comprises 3-steps including 'Goal modeling and weighting', 'Goal model monitoring', 'Goal model evaluation and analysis'. Through these research, we provide core knowledge for 'Autonomic Control system' and it is possible to increase the reliability of system by evaluating 'Goal model' with applying weight. As case study, we apply 'Goal model' to a 'Smart IoT Kit' and we demonstrate the validity of the suggested research.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2012.06a
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• pp.143-145
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• 2012

해상교통안전성평가는 크게 해양 안전 및 환경측면에서, 세부적으로는 해당해역의 특성을 파악하여 항로수립, 해상교통안전진단 및 해상교통영향평가 등을 수행 하는 측면에서 중요하다. IWRAP은 IALA Waterway Risk Assessment라는 평가도구로 항만수로의 위험도(선박의 충돌 및 좌초확률)를 분석하는 정량적인 평가모델이다. 정량적인 해상안전 평가방법은 통항량, 선속, 길이, 선박의 통항분포로부터 해상에서 통항의 위험도를 평가하므로 인적, 지리적, 환경적 등 주관적인 요소들이 많은 정성적인 평가방법에 비해 적용이 간단하다. 본 연구에서는 IWRAP을 해상교통안전진단제도로의 활용을 위해 목포항 진입수로를 대상으로 IWRAP분석을 하여 그 실효성을 평가 하고자 한다.

• Journal of the Korea Institute of Building Construction
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• v.17 no.3
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• pp.287-294
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• 2017

Recently the construction project is becoming large-sized, complicated, and modernize. This has increased the uncertainty of construction risk. Therefore, studies should be followed regarding scientifically identifying the risk factors, quantifying the frequency and severity of risk factors in order to develop a model that can quantitatively evaluate and manage the risk for response the increased risk in construction. To address the problem, this study analyze the probability distribution of risk causes, the probability of occurrence and frequency of the specific risk level through Monte Carlo simulation method based on the accident data caused at construction sites. In the end, this study derives quantitative analysis by analyzing the amount of risk and probability distributions of accident causes. The results of this study will be a basis for future quantitative risk management models and risk management research.

• Proceedings of the KSR Conference
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• 2007.05a
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• pp.605-613
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• 2007

In order to overcome the difficulties of quantitative risk analysis such as complexity of model, we propose a systematic methodology for risk quantification of railway system which consists of 6 steps: The identification of risk factors, the determination of major scenarios for each risk factor by using event tree, the development of supplementary fault trees for evaluating branch probabilities, the evaluation of event probabilities, the quantification of risk, and the analysis in consideration of accident situation. In this study, in order to address the feasibility of the propose methodology, this framework is applied to the prototype risk model of nation-wide railway level crossings. And the quantification result based on the data of 2005 in Korea will also be presented.

• International Journal of Highway Engineering
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• v.4 no.4 s.14
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• pp.1-12
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• 2002

Pavement Management System has a special purpose that the rehabilitation strategy applied on pavement should be executable in view of technical and economical point after new pavement open to the traffic. To achieve that purpose, a reliable pavement performance prediction model should be embeded in the system. The object of this study is to develop a probabilistic pavement performance prediction model for evaluating asphalt pavements based on the Markov chain concept. In this paper, methodology of the Markov chain modeling principle is explained, and the application of this model to asphalt pavement is described. As the results, transition matrics for predicting asphalt pavement performance are obtained, and also performance life is estimated quantitatively by this system.

• Fire Science and Engineering
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• v.30 no.5
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• pp.116-123
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• 2016

The quantitative risk assessment methods for thermal failure in targets were studied using fire modeling. To this end, Fire Dynamics Simulator (FDS), as a representative fire model, was used and the probabilities related to thermal damage to an electrical cable were evaluated according to the change in fire area inside a specific compartment. 'The maximum probability of exceeding the damage thresholds' adopted in a conservative point of view and 'the probability of failure' including the time to damage were compared. The probability of failure suggested in the present study could evaluate the quantitative fire risk more realistically, compared to the maximum probability of exceeding the damage thresholds with the assumption that thermal damage occurred the instant the target reached its minimum failure criteria in terms of the surface temperature and heat flux.