• 방사성폐기물학회지
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• 제18권spc호
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• pp.63-74
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• 2020

The operational safety assessment is an important part of a safety case for the deep geological repository of spent fuels. It consists of different stages such as the identification of initiating events, event tree analysis, fault tree analysis, and evaluation of exposure doses to the public and radiation workers. This study develops a probabilistic safety assessment method for the operational safety assessment and establishes an assessment framework. For the event and fault tree analyses, we propose the advanced information management system for probabilistic safety assessment (AIMS-PSA Manager). In addition, we propose the Radiological Safety Analysis Computer (RSAC) program to evaluate exposure doses to the public and radiation workers. Furthermore, we check the applicability of the assessment framework with respect to drop accidents of a spent fuel assembly arising out of crane failure, at the surface facility of the KRS⁺ (KAERI Reference disposal System for SNFs). The methods and tools established through this study can be used for the development of a safety case for the KRS⁺ system as well as for the design modification and the operational safety assessment of the KRS⁺ system.

• 한국공작기계학회논문집
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• 제17권6호
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• pp.77-82
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• 2008

This paper presents a Reliability-Based Topology Optimization(RBTO) using the Evolutionary Structural Optimization(ESO). An actual design involves some uncertain conditions such as material property, operational load and dimensional variation. The Deterministic Topology Optimization(DTO) is obtained without considering the uncertainties related to the uncertainty parameters. However, the RBTO can consider the uncertainty variables because it has the probabilistic constraints. In order to determine whether the probabilistic constraints are satisfied or not, simulation techniques and approximation methods are developed. In this paper, the reliability index approach(RIA) is adopted to evaluate the probabilistic constraints. In order to apply the ESO method to the RBTO, sensitivity number is defined as the change in the reliability index due to the removal of the ith element. Numerical examples are presented to compare the DTO with the RBTO.

• 한국자기학회지
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• 제26권3호
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• pp.81-85
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• 2016

본 논문에서는 제작공차에 의해 전기기기 및 소자 관련 제품에서 발생하는 성능함수의 변동특성을 예측하기 위해서 성능 모멘트 적분법을 도입하였다. 성능함수의 확률론적 분포특성을 판단할 수 있는 평균과 분산을 효율적으로 계산하기 위해서 정규분포로 변환된 성능함수 공간과 혼합형 평균치 기법을 채용하였다. 제안된 기법의 수치적인 효율성과 정밀도를 검증하기 위해서 간단한 수학예제와 스피커 모델에 적용하여 예측된 성능함수의 확률분포 특성을 차원감소법과 몬테카를로 수치모사법의 결과와 비교하였다.

• Nuclear Engineering and Technology
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• 제49권2호
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• pp.360-372
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• 2017

Many advanced reactor designs rely on passive systems to fulfill safety functions during accident sequences. These systems depend heavily on boundary conditions to induce a motive force, meaning the system can fail to operate as intended because of deviations in boundary conditions, rather than as the result of physical failures. Furthermore, passive systems may operate in intermediate or degraded modes. These factors make passive system operation difficult to characterize within a traditional probabilistic framework that only recognizes discrete operating modes and does not allow for the explicit consideration of time-dependent boundary conditions. Argonne National Laboratory has been examining various methodologies for assessing passive system reliability within a probabilistic risk assessment for a station blackout event at an advanced small modular reactor. This paper provides an overview of a passive system reliability demonstration analysis for an external event. Considering an earthquake with the possibility of site flooding, the analysis focuses on the behavior of the passive Reactor Cavity Cooling System following potential physical damage and system flooding. The assessment approach seeks to combine mechanistic and simulation-based methods to leverage the benefits of the simulation-based approach without the need to substantially deviate from conventional probabilistic risk assessment techniques. Although this study is presented as only an example analysis, the results appear to demonstrate a high level of reliability of the Reactor Cavity Cooling System (and the reactor system in general) for the postulated transient event.

• 한국해양공학회지
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• 제32권4호
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• pp.215-221
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• 2018

In this study, the optimal design of a mooring system was carried out. Unlike almost all design methods, which are based on the deterministic method, this study focused on the probabilistic method. The probabilistic method, especially the design of experiment (DOE), could be a good way to cover some of the drawbacks of the deterministic approach. There various parameters for a mooring system, as widely known, including the weight, length, and stiffness of line. Scenarios for the mooring system parameters were produced using the Latin Hypercube Sampling method of the probabilistic approach. Next, a vessel-mooring system coupled analysis was performed in Orcaflex. A total of 50 scenarios were used in this study to optimize the initial design by means of a genetic algorithm. Finally, after determining the optimal process, a reliability analysis was performed to understand the system validity.

• 품질경영학회지
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• 제41권1호
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• pp.149-162
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• 2013

Purpose: The purpose of this study was to design of a probabilistic model for optimum manpower planning in R&D department by Montecarlo simulation. Methods: We investigate the process and the requirement of manpower planning and scheduling in R&D department. The empirical distributions of necessary time and manpower for R&D projects are developed. From the empirical distributions, we can estimate a probability distribution of optimum manpower in R&D department. A simulation method of estimating the probability distribution of optimum manpower is considered. It is a useful tool for obtaining the sum, the variance and other statistics of the distributions. Results: The real industry cases are given and the properties of the model are investigated by Montecarlo Simulation. we apply the model to the research laboratory of the global company, and investigate and compensate the weak points of the model. Conclusion: The proposed model provides various and correct information such as average, variance, percentile, minimum, maximum and so on. A decision maker of a company can easily develop the future plan and the task of researchers may be allocated properly. we expect that the productivity can be improved by this study. The results of this study can be also applied to other areas including shipbuilding, construction, and consulting areas.

• Journal of Construction Engineering and Project Management
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• 제1권1호
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• pp.37-43
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• 2011

Labor productivity is a significant factor associated with controlling time, cost, and quality. Many researchers have developed models to define methods of measuring the relationship between productivity and various parameters such as the size of working area, maximum working hours, and the crew composition. Most of the previous research has focused on estimating productivity; however, this research concentrates on estimating labor productivity and developing time and cost data for repetitive concrete pouring activity. In Korea, "Standard Estimating" only entails the average productivity data of the construction industry, and it is difficult to predict the time and cost spent on any particular project. As a result, errors occur in estimating duration and cost for individual activities or projects. To address these issues, this research sought to collect data, measure productivity, and develop time and cost data using labor productivity based on field conditions from the collected data. A probabilistic approach is also proposed to develop data. A case study is performed to validate this process using actual data collected from construction sites. It is possible that the result will be used as the EVMS baseline of cost management and schedule management.

• 대한조선학회논문집
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• 제55권2호
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• pp.93-102
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• 2018

Quantitative Risk Assessment (QRA) has been used in shipping and offshore industries for many years, supporting the decision-making process to guarantee safe running at different stages of design, fabrication and throughout service life. The assessments of a risk perspective are informed by the frequency of events (probability) and the associated consequences. As the number of offshore platforms increases, so does the length of subsea pipelines, thus there is a need to extend this approach and enable the subsea industry to place more emphasis on uncertainties. On-board operations can lead to objects being dropped on subsea pipelines, which can cause leaks and other pipeline damage. This study explains how to conduct hit frequency analyses of subsea pipelines, using historical data, and how to obtain a finite number of scenarios for the consequences analysis. An example study using probabilistic methods is used.

• Communications for Statistical Applications and Methods
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• 제24권2호
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• pp.143-154
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• 2017

A variable selection method based on probabilistic principal component analysis (PCA) using penalized likelihood method is proposed. The proposed method is a two-step variable reduction method. The first step is based on the probabilistic principal component idea to identify principle components. The penalty function is used to identify important variables in each component. We then build a model on the original data space instead of building on the rotated data space through latent variables (principal components) because the proposed method achieves the goal of dimension reduction through identifying important observed variables. Consequently, the proposed method is of more practical use. The proposed estimators perform as the oracle procedure and are root-n consistent with a proper choice of regularization parameters. The proposed method can be successfully applied to high-dimensional PCA problems with a relatively large portion of irrelevant variables included in the data set. It is straightforward to extend our likelihood method in handling problems with missing observations using EM algorithms. Further, it could be effectively applied in cases where some data vectors exhibit one or more missing values at random.

• 한국콘크리트학회:학술대회논문집
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• 한국콘크리트학회 2008년도 춘계 학술발표회 제20권1호
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• pp.545-548
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• 2008

염해에 의한 철근부식은 구조물의 내구성능을 결정하는 주요 인자로써, 염해에 노출된 해양 구조물은 이에 대비하여 내구성 설계를 해야 한다. 내구성 설계 방법에는 결정론적방법론과 확률론적 방법론이 있으며, 정확한 내구수명의 예측을 위해서는 염화물의 농도와 확산특성에 대한 정확한 자료가 필수적이다. 최근에는 확률론적 방법론에 기반한 염해 내구성 설계에 대한 연구가 많이 수행되고 있으나, 이러한 설계 기법에 필수적인 염해관련 물성치들에 대한 통계자료의 축적은 미비한 실정이다. 따라서, 본 연구에서는 해양 구조물에 주로 사용되는 혼화재를 혼입한 콘크리트의 염소이온 확산계수와 이에 대한 분석을 통해 보통 시멘트, 슬래그 시멘트, 3성분계 시멘트를 사용한 콘크리트의 확산계수와 시간의존성 계수의 통계적 분포를 도출하였다.