• 디지털융복합연구
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• 제15권4호
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• pp.181-190
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• 2017

최근 가습기살균제 사건을 비롯하여 휴대폰, 유아용 기저귀 등 생활용품의 안전사고가 빈번히 발생하고 있다. 이러한 사고로부터 소비자를 보호하기 위해서는 제품 안전관리가 필요하며, 제품의 안전성 정도를 평가할 수 있는 제품 리스크 평가 도구가 필요하다. 본 논문은 한국소비자원의 제품 사고관련 위해정보를 바탕으로 제품 리스크를 평가할 수 있는 시스템인 RAS(Risk Assessment System)를 구축하였다. RAS는 사고관련 정보를 분석하는 위해정보 분석시스템과 이 시스템으로부터 도출된 정보를 활용하여 리스크를 평가하는 리스크 평가시스템으로 구성되어 있다. 리스크 평가과정에서 제품 리스크에 영향을 미치는 인과관계를 반영한 베이지안 네트워크 기반의 확률적 기법을 적용하였다. RAS를 사용하여 어린이 제품 33품목에 대해 평가를 실시했으며 EU RAPEX의 RAG의 평가결과와 비교해 보았다. 그 결과 본 연구의 RAS의 결과는 전반적으로 EU RAPEX RAG의 평가 결과에 비해 낮은 수준을 보임을 알 수 있었다. 추후과제로는 사고영향척도 입력값의 주관성 저감, 위해정보 분석시스템과 리스크 평가시스템의 연동 등을 들 수 있다.

• 설비공학논문집
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• 제25권2호
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• pp.70-78
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• 2013

Plants which are having conditions of high temperature and pressure always are exposed to danger. In order to prevent unexpected accidents, safety management that can effectively and appropriately examine facilities is required in plant operation. RBI(Risk-Based Inspection) technology in API 581 is one of standard management technique for evaluating risk on petroleum plants. There are qualitative and quantitative assessments in RBI methodology. Quantitative evaluation step is complex and required much information, so high-risk facilities in plant are selected firstly by qualitative method. Qualitative RBI is performed by choosing the answer in prepared questionnaire. However, it is difficult to believe thoroughly results from survey including ambiguous information. In this study, the procedure of qualitative RBI analysis with considering probability distribution concept were proposed by using Monte Carlo simulation method in order to increase reliability in spite of uncertain factors. In addition, qualitative risk of cooling system for LNG plant was evaluated using proposed procedure. Although 20 items of total 39 assessment items are applied to uncertain factors, risk section of high probability(89%) were verified. The detailed results were described in manuscript.

• Earthquakes and Structures
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• 제15권4호
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• pp.431-441
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• 2018

This study provides fragility-based assessment of seismic performance of reinforced concrete bridges. Seismic fragility curves were created using nonlinear analysis (NA) and artificial neural networks (ANNs). Nonlinear response history analyses were performed, in order to calculate the seismic performances of the bridges. To this end, 306 bridge-earthquake cases were considered. A multi-layered perceptron (MLP) neural network was implemented to predict the seismic performances of the selected bridges. The MLP neural networks considered herein consist of an input layer with four input vectors; two hidden layers and an output vector. In order to train ANNs, 70% of the numerical results were selected, and the remained 30% were employed for testing the reliability and validation of ANNs. Several structures of MLP neural networks were examined in order to obtain suitable neural networks. After achieving the most proper structure of neural network, it was used for generating new data. A total number of 600 new bridge-earthquake cases were generated based on neural simulation. Finally, probabilistic seismic safety analyses were conducted. Herein, fragility curves were developed using numerical results, neural predictions and the combination of numerical and neural data. Results of this study revealed that ANNs are suitable tools for predicting seismic performances of RC bridges. It was also shown that yield stresses of the reinforcements is one of the important sources of uncertainty in fragility analysis of RC bridges.

• Nuclear Engineering and Technology
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• 제37권3호
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• pp.259-264
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• 2005

This paper presents a vital area identification (VAI) method based on the current fault tree analysis (FTA) and probabilistic safety assessment (PSA) techniques for the physical protection of nuclear power plants. A structured framework of a top event prevention set analysis (TEPA) application to the VAI of nuclear power plants is also delineated. One of the important processes for physical protection in a nuclear power plant is VAI that is a process for identifying areas containing nuclear materials, structures, systems or components (SSCs) to be protected from sabotage, which could directly or indirectly lead to core damage and unacceptable radiological consequences. A software VIP (Vital area Identification Package based on the PSA method) is being developed by KAERI for the VAI of nuclear power plants. Furthermore, the KAERI fault tree solver FTREX (Fault Tree Reliability Evaluation eXpert) is specialized for the VIP to generate the candidates of the vital areas. FTREX can generate numerous MCSs for a huge fault tree with the lowest truncation limit and all possible prevention sets.

• 대한기계학회논문집A
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• 제30권9호
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• pp.1041-1048
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• 2006

The pulley is one of core mechanical elements in the power steering system for vehicles. The pulley operates under both the compressive loading and the torque. Therefore, to assure the safety of the power steering system, it is very important to investigate the durability and the optimization of the pulley. In this study, the applied stress distribution of the pulley under high tension and torsion loads was obtained by using finite element analysis. Based on these results the fatigue life of the pulley with the variation of the fatigue strength was evaluated by a durability analysis simulator. The results at 50% and 1% for the failure probability were compared with respect to the fatigue life. In addition to the optimum design for the fatigue life is obtained by the response surface method. The response function utilizes the function of the life and weight factors. Within range for design life condition the minimization of the weight, one of the formulation, is obtained by the optimal design. Moreover the optimum design by considering its durability and validity is verified by the durability test.

• Nuclear Engineering and Technology
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• 제53권2호
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• pp.386-392
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• 2021

MACCS (MELCOR Accident Consequence Code System), WinMACCS, and MelMACCS now facilitate a multi-unit consequence analysis. MACCS evaluates the consequences of an atmospheric release of radioactive gases and aerosols into the atmosphere and is most commonly used to perform probabilistic safety assessments (PSAs) and related consequence analyses for nuclear power plants (NPPs). WinMACCS is a user-friendly preprocessor for MACCS. MelMACCS extracts source-term information from a MELCOR plot file. The current development can combine an arbitrary number of source terms, representing simultaneous releases from a multi-unit facility, into a single consequence analysis. The development supports different release signatures, fission product inventories, and accident initiation times for each unit. The treatment is completely general except that the model is currently limited to collocated units. A major practical consideration for performing a multi-unit PSA is that a comprehensive treatment for more than two units may involve an intractable number of combinations of source terms. This paper proposes and evaluates an approach for reducing the number of calculations to be tractable, even for sites with eight or ten units. The approximation error introduced by the approach is acceptable and is considerably less than other errors and uncertainties inherent in a Level 3 PSA.

• Structural Engineering and Mechanics
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• 제63권6호
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• pp.809-824
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• 2017

The accurate evaluation of wind characteristics and wind-induced structural responses during a typhoon is of significant importance for bridge design and safety assessment. This paper presents an expectation maximization (EM) algorithm-based angular-linear approach for probabilistic modeling of field-measured wind characteristics. The proposed method has been applied to model the wind speed and direction data during typhoons recorded by the structural health monitoring (SHM) system instrumented on the arch Jiubao Bridge located in Hangzhou, China. In the summer of 2015, three typhoons, i.e., Typhoon Chan-hom, Typhoon Soudelor and Typhoon Goni, made landfall in the east of China and then struck the Jiubao Bridge. By analyzing the wind monitoring data such as the wind speed and direction measured by three anemometers during typhoons, the wind characteristics during typhoons are derived, including the average wind speed and direction, turbulence intensity, gust factor, turbulence integral scale, and power spectral density (PSD). An EM algorithm-based angular-linear modeling approach is proposed for modeling the joint distribution of the wind speed and direction. For the marginal distribution of the wind speed, the finite mixture of two-parameter Weibull distribution is employed, and the finite mixture of von Mises distribution is used to represent the wind direction. The parameters of each distribution model are estimated by use of the EM algorithm, and the optimal model is determined by the values of $R^2$ statistic and the Akaike's information criterion (AIC). The results indicate that the stochastic properties of the wind field around the bridge site during typhoons are effectively characterized by the proposed EM algorithm-based angular-linear modeling approach. The formulated joint distribution of the wind speed and direction can serve as a solid foundation for the purpose of accurately evaluating the typhoon-induced fatigue damage of long-span bridges.

• 한국생산제조학회지
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• 제19권4호
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• pp.529-538
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• 2010

This paper presents a reliability-based topology optimization (RBTO) based on bidirectional evolutionary structural optimization (BESO). In design of a structure, uncertain conditions such as material property, operational load and dimensional variation should be considered. Deterministic topology optimization (DTO) is performed without considering the uncertainties related to the design variables. However, the RBTO can consider the uncertainty variables because it can deal with the probabilistic constraints. The reliability index approach (RIA) and the performance measure approach (PMA) are adopted to evaluate the probabilistic constraints in this study. In order to apply the BESO to the RBTO, sensitivity number for each element is defined as the change in the reliability index of the structure due to removal of each element. Smoothing scheme is also used to eliminate checkerboard patterns in topology optimization. The limit state indicates the margin of safety between the resistance (constraints) and the load of structures. The limit State function expresses to evaluate reliability index from finite element analysis. Numerical examples are presented to compare each optimal topology obtained from RBTO and DTO each other. It is verified that the RBTO based on BESO can be effectively performed from the results.

• 한국지진공학회논문집
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• 제23권6호
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• pp.289-299
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• 2019

The tendency to use a probabilistic design method rather than a deterministic design method for the design of nuclear power plants (NPPs) will increase because their safety should be considered and strictly controlled in relation to various causes of damage. The distance between a seismically isolated NPP structure and a moat wall is called the clearance to stop. The clearance to stop is obtained from the 90th percentile displacement response of a seismically isolated NPP subject to a beyond design basis earthquake (BDBE) in the probabilistic design method. The purpose of this study is to analyze the effects of heating and buckling effects on the 90th percentile displacement response of a lead-rubber bearing (LRB) subject to a BDBE. The analysis results show that considering the heating and buckling effects to estimate the clearance to stop is conservative in the evaluation of the 90th percentile displacement response. If these two effects are not taken into account in the calculation of the clearance to stop, the underestimation of the clearance to stop causes unexpected damage because of an increase in the collision probability between the moat wall and the seismically isolated NPP.

• 한국전산구조공학회논문집
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• 제32권2호
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• pp.93-101
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• 2019

이 연구의 목적은 인공신경망 기법을 이용하여 사면의 내진 성능을 비교적 정확하면서도 효율적으로 예측하는 모델을 도출하는데 있다. 사면의 내진 성능은 지진입력 및 사면모델의 무작위성 및 불확실성으로 인하여 정량화하기 쉽지 않다. 이러한 배경 아래 사면에 대한 확률론적 지진 취약도 분석이 몇몇 연구자에 의해 수행되었고, 이를 기반으로 다중 선형회귀분석을 통하여 사면 내진성능에 대한 닫힌식이 제안된 바 있다. 그러나 전통적인 통계학적 선형회귀분석은 다양한 조건의 사면과 이에 따른 내진 성능 사이의 비선형적 관계를 정확하게 표현하지 못하는 한계를 보였다. 이에 따라 본 연구에서는 이러한 문제점을 극복하고자 인공신경망 기법을 사면 내진성능 예측 모델을 생성하는데 적용하였다. 도출된 모델의 유효성은 기존의 다중 선형 및 다중 비선형 회귀분석을 통한 모델과 비교하여 검증하였다. 결과적으로 이전 연구의 전통적인 통계학적 회귀 분석을 통한 모델과 비교 결과, 기본적으로 인공신경망 기법을 통하여 도출된 모델이 사면의 내진성능을 예측하는데 있어 우수한 성능을 보여주었다. 이러한 정확도 높은 모델은 향후 확률에 기반한 사면의 지진취약도 지도를 개발하고, 주요 구조물의 인근 사면으로 인한 리스크를 효과적으로 평가하는데 활용될 수 있을 것이라 기대된다.