• Geomechanics and Engineering
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• 제18권6호
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• pp.661-668
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• 2019

Seismic vulnerability assessment is a useful tool for rational safety analysis and planning of large and complex structural systems; it can deal with the effects of uncertainties on the performance of significant structural systems. In this study, an efficient dynamic reliability approach, probability density evolution methodology (PDEM), is proposed for seismic vulnerability analysis of earth dams. The PDEM provides the failure probability of different limit states for various levels of ground motion intensity as well as the mean value, standard deviation and probability density function of the performance metric of the earth dam. Combining the seismic reliability with three different performance levels related to the displacement of the earth dam, the seismic fragility curves are constructed without them being limited to a specific functional form. Furthermore, considering the seismic fragility analysis is a significant procedure in the seismic probabilistic risk assessment of structures, the seismic vulnerability results obtained by the dynamic reliability approach are combined with the results of probabilistic seismic hazard and seismic loss analysis to present and address the PDEM-based seismic probabilistic risk assessment framework by a simulated case study of an earth dam.

• 한국식품과학회지
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• 제42권3호
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• pp.373-376
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• 2010

본 연구는 국내에서의 가정내 냉장고 온도에 대한 조사를 수행하여, 현 시점에서의 냉장고에서의 식품보관 온도분포를 추정하였고, 이를 MRA(미생물 위해평가: Microbial risk assessment)의 입력변수로 활용할 수 있도록 적정 확률분포 모델을 제시하였다. 일반적으로 가정내 냉장고에서의 식품 보관온도는 식중독 발생 등에서 있어 중요한 위해인자로 작용하는 것으로 알려져 있다. 조사대상 가구는 총 139가구이었으며, 조사기간은 2009년 5월에서부터 9월까지 data logger를 이용하여 측정하였다. 조사된 냉장고 온도의 평균은 $3.53{\pm}2.96^{\circ}C$로, $5^{\circ}C$ 이상은 23.6%로 나타났다. 수집된 온도자료는 @RISK를 이용, 적합성 검정(GOF: K-S와 AD test)을 수행하여 적정 확률분포모델에 대해 추정하였고, 이중 LogLogistic(-10.407, 13.616, 8.6107)분포 모델이 가장 적절한 국내에서의 가정내 냉장고 식품보관 온도분포 모델로 나타났다. 이 확률분포 모델은 MRA적용에 있어 노출평가에서 입력변수로서 직접적 활용이 가능하다고 할 수 있겠다.

• 대한안전경영과학회지
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• 제14권3호
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• pp.39-48
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• 2012

Risk Assessment to list possible safety disasters and their probability and severity is the starting point for effective safety management on construction project site. However, the safety managers in owners, construction supervisors, contractors, and sub-contractors still have difficulties in judging the priorities of safety activities and preparing responses to each potential safety disasters. Therefore, this study aimed to suggest a systematic method in assessing safety risk prior to commencement with the agreement of stakeholders. FMECA(failure mode effects and criticality analysis) was selected as a main assessment tool and it was modified according to the characteristics of construction projects and trades. Each risk is, firstly, evaluated with occurrence probability, possible loss and impacts to projects, and detections, and then risk priority number(RPN) is calculated. Subsequently, the managers of each stakeholder discuss the types, timing, and responsibilities of responses as a group decision-making process.

• 한국농공학회논문집
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• 제58권3호
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• pp.57-69
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• 2016

In this study, we analyzed the extreme rainfall distribution scenarios based on probable rainfall calculation and applying various time distribution models over the landslide high risk zones in urban areas. We used observed rainfall data form total 71 ASOS (Automated Synoptic Observing System) station and AWS (Automatic Weather Station) in KMA (Korea Meteorological Administration), and we analyzed the linear trends for 1-hr and 24-hr annual maximum rainfall series using simple linear regression method, which are identified their increasing trends with slopes of 0.035 and 0.660 during 1961-2014, respectively. The Gumbel distribution was applied to obtain the return period and probability precipitation for each duration. The IDF (Intensity-Duration-Frequency) curves for landslide high risk zones were derived by applying integrated probability precipitation intensity equation. Results from IDF analysis indicate that the probability precipitation varies from 31.4~38.3 % for 1 hr duration, and 33.0~47.9 % for 24 hr duration. It also showed different results for each area. The $Huff-4^{th}$ Quartile method as well as Mononobe distribution were selected as the rainfall distribution scenarios of landslide high risk zones. The results of this study can be used to provide boundary conditions for slope collapse analysis, to analyze sediment disaster risk, and to use as input data for risk prediction of debris flow.

• Membrane and Water Treatment
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• 제8권2호
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• pp.137-147
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• 2017

A water treatment utility in South Korea operates a large system of pressurized hollow fiber membrane (PHFM) modules. The optimal selection of membrane module for the full scale plant was critical issue and carried out using Risk-based Life Cycle Cost (RbLCC) analysis based on the historical data of operation and maintenance. The RbLCC analysis was used in the process of decision-making for replacing aged modules. The initial purchasing cost and the value at risk during operation were considered together. The failure of modules occurs stochastically depending on the physical deterioration with usage over time. The life span of module was used as a factor for the failure of Poisson's probability model, which was used to obtain the probability of failure during the operation. The RbLCC was calculated by combining the initial cost and the value at risk without its warranty term. Additionally, the properties of membrane were considered to select the optimum product. Results showed that the module's life span in the system was ten years (120 month) with safety factor. The optimum product was selected from six candidates membrane for a full scale water treatment facility. This method could be used to make the optimum and rational decision for the operation of membrane water purification facility.

• 한국항공운항학회지
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• 제29권4호
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• pp.45-51
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• 2021

A runway safety area (RSA) is defined as the surface surrounding the runway prepared or suitable for reducing the risk of damage to airplanes in the event of an undershoot, overshoot, or excursion from the runway. The Runway Stripe is a defined area including the runway stopway, if provided, intended firstly to reduce the risk of damage to aircraft running off a runway, and secondly, to protect aircraft flying over it during takeoff or landing operations. This study used 2 RSA analysis models; RSARA and LRSARA. The analysis utilizes historical data from the specific airport and allows to take into consideration specific operational conditions to which movements are subject, as well as the actual or planned RSA conditions in terms of dimensions, configuration, and boundaries defined by existing obstacles. This study applied the RSA and LRSA risk assessment models to a domestic airport that do not meet the criteria required by standards for aerodrome physical characteristics. The airport is considering a method to secure the runway strip standard through the displaced threshold. This study intends to confirm through quantitative risk estimation whether meeting facility standards through the runway displaced threshold leads to a positive change in risk mitigation.

• Journal of the Korean Society for Industrial and Applied Mathematics
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• 제19권1호
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• pp.23-45
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• 2015

We consider counterparty risk in CDS rates. To do so, we use a multivariate jump diffusion process for obligors' default intensity, where jumps (i.e. magnitude of contribution of primary events to default intensities) occur simultaneously and their sizes are dependent. For these simultaneous jumps and their sizes, a homogeneous Poisson process. We apply copula-dependent default intensities of multivariate Cox process to derive the joint Laplace transform that provides us with joint survival/default probability and other relevant joint probabilities. For that purpose, the piecewise deterministic Markov process (PDMP) theory developed in [7] and the martingale methodology in [6] are used. We compute survival/default probability using three copulas, which are Farlie-Gumbel-Morgenstern (FGM), Gaussian and Student-t copulas, with exponential marginal distributions. We then apply the results to calculate CDS rates assuming deterministic rate of interest and recovery rate. We also conduct sensitivity analysis for the CDS rates by changing the relevant parameters and provide their figures.

• 한국농공학회:학술대회논문집
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• 한국농공학회 2005년도 학술발표논문집
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• pp.135-138
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• 2005

This study began to establish a risk evaluation method for irrigation reservoirs under the overtopping failure mode. To define the risk, reliability analysis was performed using time series of reservoir flood inflow and spillway outflow. The former was defined as a load and the latter was the resistance component. The method results in failure probability, which is calculated by convolution multiplication between probability distribution functions of both components. The proposed method was applied to 3 reservoir sites and each failure probability was determined as 0.0012, 0.00001, and 0.000001 respectively.

• 산업경영시스템학회지
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• 제30권3호
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• pp.37-43
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• 2007

We use influence diagrams to describe event trees used in safety analyses of low-probability high-risk incidents. This paper shows how the branch parameters used in the event tree models can be updated by a bayesian method based on the observed counts of certain well-defined subsets of accident sequences. We focus on the analysis of the shared branch parameters, which may frequently often in the real accident initiation and propagation to more severe accident. We also suggest the way to utilize different levels of accident data to forecast low-probability high-risk accidents.

• 한국축산식품학회지
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• 제39권4호
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• pp.565-575
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• 2019

This study evaluated Campylobacter jejuni risk in ground meat products. The C. jejuni prevalence in ground meat products was investigated. To develop the predictive model, survival data of C. jejuni were collected at $4^{\circ}C-30^{\circ}C$ during storage, and the data were fitted using the Weibull model. In addition, the storage temperature and time of ground meat products were investigated during distribution. The consumption amount and frequency of ground meat products were investigated by interviewing 1,500 adults. The prevalence, temperature, time, and consumption data were analyzed by @RISK to generate probabilistic distributions. In 224 samples of ground meat products, there were no C. jejuni-contaminated samples. A scenario with a series of probabilistic distributions, a predictive model and a dose-response model was prepared to calculate the probability of illness, and it showed that the probability of foodborne illness caused by C. jejuni per person per day from ground meat products was $5.68{\times}10^{-10}$, which can be considered low risk.