• 한국제4기학회지
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• 제19권2호
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• pp.74-79
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• 2005

Recently, several attempts have been made to provide reasonable information on unusual severe weather phenomena such as tolerant heavy rains and very wild typhoons. Quantitative precipitation forecasts and probabilistic quantitative precipitation forecasts (QPFs and PQPFs, respectively) might be one of the most promising methodologies for early warning on the flesh floods because those diagnostic precipitation models require less computational resources than fine-mesh full-dynamics non-hydrostatic mesoscale model. The diagnostic rainfall model used in this study is the named QPM(Quantitative Precipitation Model), which calculates the rainfall by considering the effect of small-scale topography which is not treated in the mesoscale model. We examine the capability of probabilistic diagnostic rainfall model in terms of how well represented the observed several rainfall events and what is the most optimistic resolution of the mesoscale model in which diagnostic rainfall model is nested. Also, we examine the integration time to provide reasonable fine-mesh rainfall information. When we apply this QPM directly to 27 km mesh meso-scale model (called as M27-Q3), it takes about 15 min. while it takes about 87 min. to get the same resolution precipitation information with full dynamic downscaling method (called M27-9-3). The quality of precipitation forecast by M27-Q3 is quite comparable with the results of M27-9-3 with reasonable threshold value for precipitation. Based on a series of examination we may conclude that the proosed QPM has a capability to provide fine-mesh rainfall information in terms of time and accuracy compared to full dynamical fine-mesh meso-scale model.

• Journal of Information Technology Applications and Management
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• 제16권3호
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• pp.59-71
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• 2009

Hazard analysis identifies probability to hazard occurrence and its potential impact on business processes operated in organizations. This paper illustrates a quantitative approach of hazard analysis of information systems by measuring the degree of hazard to information systems using probabilistic risk analysis and activity based costing technique. Specifically the research model projects probability of occurrence by PRA and economic loss by ABC under each identified hazard. To verify the model, each computerized subsystem which is called a business process and hazards occurred on information systems are gathered through one private organization. The loss impact of a hazard occurrence is produced by multiplying probability by the economic loss.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2005년도 춘계 학술발표회 논문집
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• pp.185-190
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• 2005

In this study, a probabilistic prediction model for debris flow occurrence was developed using a logistic regression analysis. The model can be applicable to metamorphic rocks and granite area. In order to develop the prediction model, detailed field survey and laboratory soil tests were conducted both in the northern and the southern Gyeonggi province and in Sangju, Gyeongbuk province, Korea. The six landslide triggering factors were selected by a logistic regression analysis as well as several basic statistical analyses. The six factors consist of two topographic factors and four geological and geotechnical factors. The model assigns a weight value to each selected factor. The verification results reveal that the model has 86.5% of prediction accuracy. Therefore, it is possible to predict landslide occurrence in a probabilistic and quantitative manner.

• 국제학술발표논문집
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• The 5th International Conference on Construction Engineering and Project Management
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• pp.488-493
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• 2013

Accurate initial cost estimates are essential to effective management of construction projects where many decisions are made in the course of project management by referencing the estimates. In practice, the initial estimates are frequently derived from historical actual cost data, for which standard distribution-based techniques are widely applied in the construction industry to account for risk associated with the estimates. This approach assumes the same probability distribution of estimate errors for any selected estimates. This assumption, however, is not always satisfied. In order to account for the probabilistic nature of estimate errors, an alternative method for measuring the risk associated with a selected initial estimate is developed by applying the Bayesian probability approach. An application example include demonstrates how the method is implemented. A hypothesis test is conducted to reveal the robustness of the Bayesian probability model. The method is envisioned to effectively complement cost estimating methods that are currently in use by providing benefits as follows: (1) it effectively accounts for the probabilistic nature of errors in estimates; (2) it is easy to implement by using historical estimates and actual costs that are readily available in most construction companies; and (3) it minimizes subjective judgment by using quantitative data only.

• Nuclear Engineering and Technology
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• 제51권2호
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• pp.463-478
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• 2019

The most important non-functional requirements for dependability of any Embedded Real-Time Safety Systems are safety, availability and reliability requirements. System architecture plays the primary role in achieving these requirements. Compliance with these non-functional requirements should be ensured early in the development cycle with appropriate considerations during architectural design. In this paper, we present an application of system architecture modeling for quantitative assessment of system dependability. We use probabilistic model checker (PRISM), for dependability analysis of the DTMC model derived from system architecture model. In general, the model checking techniques do not scale well for analyzing large systems, because of prohibitively large state space. It limits the use of model checking techniques in analyzing the systems of practical interest. We propose abstraction based compositional analysis methodology to circumvent this limitation. The effectiveness of the proposed methodology has been demonstrated using the case study involving the dependability analysis of safety system of a large Pressurized Water Reactor (PWR).

• Nuclear Engineering and Technology
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• 제51권1호
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• pp.138-145
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• 2019

With the application of digital technology to safety-critical infrastructures, cyber-attacks have emerged as one of the new dangerous threats. In safety-critical infrastructures such as a nuclear power plant (NPP), a cyber-attack could have serious consequences by initiating dangerous events or rendering important safety systems unavailable. Since a cyber-attack is conducted intentionally, numerous possible cases should be considered for developing a cyber security system, such as the attack paths, methods, and potential target systems. Therefore, prior to developing a risk-informed cyber security strategy, the importance of cyber-attacks and significant critical digital assets (CDAs) should be analyzed. In this work, an importance analysis method for cyber-attacks on an NPP was proposed using the probabilistic safety assessment (PSA) method. To develop an importance analysis framework for cyber-attacks, possible cyber-attacks were identified with failure modes, and a PSA model for cyber-attacks was developed. For case studies, the quantitative evaluations of cyber-attack scenarios were performed using the proposed method. By using quantitative importance of cyber-attacks and identifying significant CDAs that must be defended against cyber-attacks, it is possible to develop an efficient and reliable defense strategy against cyber-attacks on NPPs.

• 지질공학
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• 제14권2호
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• pp.211-222
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• 2004

이 연구는 자연사면에서 발생하는 토석류(debris flow)산사태의 확률론적 예측을 위해 로지스틱 회귀분석(logistic regression analysis)을 이용하여 변성 암 및 화강암 분포지에 적용할 수 있는 예측모델을 개발한 것이다. 산사태 예측모델을 개발하기 위해 경기 남ㆍ북부지역과 경북 상주지역에서 발생한 산사태 자료를 현장조사와 실내토질시험을 통해 직접 획득ㆍ분석하였다. 산사태 발생에 영향을 미치는 인자는 기초 통계분석은 물론 로지스틱 회귀분석을 실시하여 최종적으로 7개 영향인자를 선정하였다. 이들 7개 인자는 지형요소 2개와 지질 및 토질특성 요소 5개로 구성되어 있고, 각 인자별 가중치를 부여한 점이 큰 특징이다. 개발된 모델은 신뢰성 검증을 수행한 결과 90.74%의 예측율을 확보한 것으로 나타났다. 이 모델을 이용하여 산사태 발생가능성을 확률적ㆍ정량적으로 예측할 수 있게 되었다.

• 대한환경공학회지
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• 제33권7호
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• pp.544-551
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• 2011

본 연구의 목적은 미국 환경보호청에서 개발한 확률적 정량모델인 VIRULO 모델의 구성과 특성을 분석하는 것이다. 이 모델은 몬테카를로 방법을 이용하여 수리지질학적 차단벽으로써 토양의 바이러스 저감능을 평가할 수 있는 모델이다. 모델에 사용된 지배방정식은 크게 불포화 지역에서의 물의 흐름식과 바이러스의 이동식으로 구성되어 있다. 사용되는 파라미터들 중, 물의 흐름과 관련된 파라미터는 11종류의 토양에 대하여 UNSODA 데이터베이스로부터 얻어진 것 들이며, 바이러스와 관련된 파라미터 값들은 다섯 종류의 바이러스에 대하여 문헌조사를 통해 정리된 것이다. 모델은 목표로 하는 바이러스 저감 역치값과 특정 조건에서 몬테카를로 모사를 통해 얻어진 토양의 바이러스 저감인자를 비교하여, 목표로 하는 바이러스 저감 역치값에 도달하지 못하는 확률을 결정한다. 그리고, 몬테카를로 모사횟수와 목표 역치값에 도달하지 못한 횟수를 결과물로 제시한다. 11개의 USDA 토양을 대상으로 바이러스 저감을 평가한 결과, 양질사토와 모래의 바이러스 저감능이 점토나 미사 계열의 토양에 비하여 상당히 떨어지는 것으로 평가되었다. 5종의 바이러스를 대상으로 저감을 비교한 결과, 바이러스 간에 저감 정도에 차이가 있는 것으로 나타났으며, 그 중 폴리오바이러스의 저감 정도가 가장 큰 것으로 분석되었다. 그리고, 토양 함수량이 증가함에 따라 토양의 바이러스 저감능이 급격하게 감소하였으며, 토양의 깊이가 증가함에 따라 바이러스 저감능이 비선형적으로 증가하였다. 본 연구에 의하면, VIRULO 모델은 지중환경에서의 바이러스 위해성 평가에 사용될 수 있는 유용한 스크리닝 도구로 판단된다.

• Asian-Australasian Journal of Animal Sciences
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• 제32권2호
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• pp.274-281
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• 2019

Objective: The objective of this study was to estimate the risk of Campylobacter jejuni (C. jejuni) infection from various jerky products in Korea. Methods: For the exposure assessment, the prevalence and predictive models of C. jejuni in the jerky and the temperature and time of the distribution and storage were investigated. In addition, the consumption amounts and frequencies of the products were also investigated. The data for C. jejuni for the prevalence, distribution temperature, distribution time, consumption amount, and consumption frequency were fitted with the @RISK fitting program to obtain appropriate probabilistic distributions. Subsequently, the dose-response models for Campylobacter were researched in the literature. Eventually, the distributions, predictive model, and dose-response model were used to make a simulation model with @RISK to estimate the risk of C. jejuni foodborne illness from the intake of jerky. Results: Among 275 jerky samples, there were no C. jejuni positive samples, and thus, the initial contamination level was statistically predicted with the RiskUniform distribution [RiskUniform (-2, 0.48)]. To describe the changes in the C. jejuni cell counts during distribution and storage, the developed predictive models with the Weibull model (primary model) and polynomial model (secondary model) were utilized. The appropriate probabilistic distribution was the BetaGeneral distribution, and it showed that the average jerky consumption was 51.83 g/d with a frequency of 0.61%. The developed simulation model from this data series and the dose-response model (Beta Poisson model) showed that the risk of C. jejuni foodborne illness per day per person from jerky consumption was $1.56{\times}10^{-12}$. Conclusion: This result suggests that the risk of C. jejuni in jerky could be considered low in Korea.

• 한국구조물진단유지관리공학회 논문집
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• 제22권1호
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• pp.32-39
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• 2018

염해에 따라 발생하는 보수시기와 보수로 유지되는 내구수명은 보수비용 평가에 매우 중요한 요소이다. 일반적으로 사용하는 결정론적 보수비용 평가는 사용기간의 연장에 따라 계단식으로 증가하게 되며, 보수로 인해 변동되는 내구수명의 변화를 고려하지 못한다. 본 연구에서는 확률론적인 보수시기 및 비용을 평가하기 위해, 염해에 노출된 콘크리트 교각을 선정하였다. 두 가지 배합과 염화물에 노출된 외부 환경조건을 고려하여 염화물 거동을 평가하였으며, 도출된 내구수명과 수명에 대한 확률변수를 변화시키면서 보수시기 및 비용 변화를 분석하였다. 변동계수의 변화에 따른 보수회수는 큰 차이가 발생하지 않았으나, 초기의 내구수명 연장이 구조물의 보수시기 및 비용에 큰 영향을 미치고 있었다. 또한 확률론적 보수비용 산정 모델은 결정론적 모델과 다르게 연속적인 보수비용이 평가되므로 목표내구수명에 따라 보수회수를 감소시킬 수 있는 효과적인 기법임을 규명되었다.