• Composites Research
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• 제26권1호
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• pp.29-35
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• 2013

복합재료 샌드위치 구조는 굽힘 강성을 향상시키고 복합재 적층판에 비해 30% 이상의 무게를 절감할 수 있다. 그러나 일반 금속에 비해 제작과정에서 발생되는 재료물성의 불확실성이 많이 내재되어 있으므로 신뢰성 기반 확률론적 설계방법이 요구된다. 본 논문에서는 안전계수를 이용한 고전적인 설계 방법이 구조물의 안전을 보장하지 않는다는 확률론적 증거를 제시하기 위하여 단순화된 복합재 샌드위치 동체에 대해 PMS(Probabilistic Margin of Safety)를 계산하였다. 이 과정에서 CMCS(Crude Monte-Carlo Simulation)에 의해 계산된 확률밀도함수를 이용하였다. 더 나아가 신뢰성 기반 최적설계를 수행하고 효율적인 계산을 위해 RBDO-MPDF(RBDO by Moving PDF) 방법을 제시하였다. 본 논문의 결과는 구조물의 신뢰성을 보장하기 위한 개선된 설계 방법과 효율적인 신뢰성 기반 최적설계 방법 연구에 유용할 것이다.

• 한국안전학회지
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• 제36권2호
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• pp.101-110
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• 2021

This paper presents the results of an initiating event analysis as part of a Level 1 probabilistic safety assessment (PSA) for at-power internal events for the Korea Research Reactor (KRR). The PSA methodology is widely used to quantitatively assess the safety of research reactors (RRs) in the domestic nuclear industry. Initiating event frequencies are required to conduct a PSA, and they considerably affect the PSA results. Because there is no domestic database for domestic trip events, the safety of RRs is usually assessed using foreign databases. In this paper, operating experience data from the KRR for trip events were collected and analyzed in order to determine the frequency of specific initiating events. These frequencies were calculated using two approaches according to the event characteristics and data availability: (1) based on KRR operating experience or (2) using generic data.

• 한국지진공학회논문집
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• 제25권2호
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• pp.53-58
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• 2021

Nuclear power plant's safety against seismic events is evaluated as risk values by probabilistic seismic safety assessment. The risk values vary by the seismic failure correlation between the structures, systems, and components (SSCs). However, most probabilistic seismic safety assessments idealized the seismic failure correlation between the SSCs as entirely dependent or independent. Such a consideration results in an inaccurate assessment result not reflecting real physical phenomenon. A nuclear power plant's seismic risk should be calculated with the appropriate seismic failure correlation coefficient between the SSCs for a reasonable outcome. An accident scenario that has an enormous impact on a nuclear power plant's seismic risk was selected. Moreover, the probabilistic seismic response analyses of a nuclear power plant were performed to derive appropriate seismic failure correlations between SSCs. Based on the analysis results, the seismic failure correlation coefficient between SSCs was derived, and the seismic fragility curve and core damage frequency of the loss of essential power event were calculated. Results were compared with the seismic fragility and core damage frequency of assuming the seismic failure correlations between SSCs were independent and entirely dependent.

• Nuclear Engineering and Technology
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• 제53권11호
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• pp.3465-3473
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• 2021

For a long time, research into integrated deterministic-probabilistic safety assessment has been continuously conducted to point out and overcome the limitations of classical ET (event tree)/FT (fault tree) based PSA (probabilistic safety assessment). The current paper also attempts to assert the reason why a technical transformation from classical PSA is necessary with a re-interpretation of the categories of risk. In this study, residual risk was classified into interpolating- and extrapolating-censored categories, which represent risks that are difficult to identify through an interpolation or extrapolation of representative scenarios due to potential nonlinearity between hardware and human behaviors intertwined in time and space. The authors hypothesize that such risk can be dealt with only if the classical ETs/FTs are freely relocated, entailing large-scale computation associated with physical models. The functional elements that are favorable to find residual risk were inferred from previous studies. The authors then introduce their under-development enabling techniques, namely DICE (Dynamic Integrated Consequence Evaluation) and DeBATE (Deep learning-Based Accident Trend Estimation). This work can be considered as a preliminary initiative to find the bridging points between deterministic and probabilistic assessments on the pillars of big data technology.

• Nuclear Engineering and Technology
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• 제50권8호
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• pp.1217-1233
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• 2018

Following a surge of interest in multi-unit risk in the last few years, many recent studies have suggested methods for multi-unit probabilistic safety assessment (MUPSA) and addressed several related aspects. Most of the existing studies though focused on two-unit nuclear power plant (NPP) sites or used rather simplified probabilistic safety assessment (PSA) models to demonstrate the proposed approaches. When considering an NPP site with three or more units, some approaches are inapplicable or yield very conservative results. Since the number of such sites is increasing, there is a strong need to develop and validate practical approaches to the related MUPSA. This article provides several detailed approaches that are applicable to multi-unit Level 1 PSA for sites with up to six or more reactor units. To validate the approaches, a multi-unit Level 1 PSA model is developed and the site core damage frequency is estimated for each of four representative multi-unit initiators, as well as for the case of a simultaneous occurrence of independent single-unit initiators in multiple units. For this purpose, an NPP site with six identical OPR-1000 units is considered, with full-scale Level 1 PSA models for a specific OPR-1000 plant used as the base single-unit models.

• 한국안전학회지
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• 제25권6호
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• pp.186-196
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• 2010

It has been well known that traffic accidents occur under combined functional contributions of drivers, vehicles and road facilities, and that evaluation of safety levels for a specific road section or point is generally much complicated. Additionally, most of traffic accidents occur randomly implicating it is necessary to be evaluated in terms of probability theory. Thus, the evaluation model which reflects various characteristics and probabilistic distributions of traffic accidents has been necessary. The present paper provides a reliability based model with variables of probabilistic operating speeds and design speeds together which have been individually explaining associated characteristics in traffic accidents. Consequently, the model made it possible for speed management and road improvement projects to be evaluated in a common index. Application studies were performed in three cases. Through the studies, couples of facts were identified that the model successfully considered the probabilistic operating speeds and design speeds together and that then, the model evaluated road safety alternatives relatively which are complicatedly characterized and differently located.

• 한국신뢰성학회지:신뢰성응용연구
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• 제18권3호
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• pp.271-279
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• 2018

Purpose: Probabilistic safety analysis was performed to enhance the safety and reliability of nuclear power plants because traditional deterministic approach has limitations in predicting the risk of failure by crack growth. The study introduces a probabilistic approach to establish a basis for probabilistic safety assessment of passive components. Methods: For probabilistic modeling of fatigue crack growth rate (FCGR), various FCGR tests were performed either under constant load amplitude or constant ${\Delta}K$ conditions by using heat treated X-750 at low temperature with adequate cathodic polarization. Bayesian inference was employed to update uncertainties of the FCGR model using additional information obtained from constant ${\Delta}K$ tests. Results: Four steps of Bayesian parameter updating were performed using constant ${\Delta}K$ test results. The standard deviation of the final posterior distribution was decreased by a factor of 10 comparing with that of the prior distribution. Conclusion: The method for developing a probabilistic crack growth model has been designed and demonstrated, in the paper. Alloy X-750 has been used for corrosion fatigue crack growth experiments and modeling. The uncertainties of parameters in the FCGR model were successfully reduced using the Bayesian inference whenever the updating was performed.

• 전산구조공학
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• 제2권4호
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• pp.89-98
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• 1989

구조해석에 사용되는 변수들이 갖고 있는 통계적 특성을 고려하기 위해 기존의 방법에서는 경험에 입각한 안전계수를 사용하여, 변수가 갖고 있는 불확실성을 정성적으로 취급하여 구조물의 안전성을 점검하여 왔다. 그러나, 최근 확률이론에 입각한 신뢰성이론을 적용하여 구조물의 안전성을 보다 정량적으로 파악하여 충분한 경험과 실적이 부족한 새로운 형태의 구조물의 안전성 점검에도 활용하려는 시도가 많이 이루어지고 있다. 이러한 추세에 따라, 본 연구에서는 기존의 유한요소법에 확률론적 수법을 가미한 확률 유한요소법을 개발하여, 구조해석에 사용되는 변수들이 갖고 있는 불확실량들이 구조해석의 최종결과에 어떤 영향을 미치는가를 확률적으로 처리하여, 구조물의 안전성을 보다 합리적으로 평가하도록 하였다.

• Nuclear Engineering and Technology
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• 제54권6호
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• pp.2084-2093
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• 2022

Probabilistic safety assessment is widely used to quantify the risks of nuclear power plants and their uncertainties. When the lognormal distribution describes the uncertainties of basic events, the uncertainty of the top event in a fault tree is approximated with the sum of lognormal random variables after minimal cutsets are obtained, and rare-event approximation is applied. As handling complicated analytic expressions for the sum of lognormal random variables is challenging, several approximation methods, especially Monte Carlo simulation, are widely used in practice for uncertainty analysis. In this study, a theoretical approach for analyzing the sum of lognormal random variables using an efficient numerical integration method is proposed for uncertainty analysis in probability safety assessments. The change of variables from correlated random variables with a complicated region of integration to independent random variables with a unit hypercube region of integration is applied to obtain an efficient numerical integration. The theoretical advantages of the proposed method over other approximation methods are shown through a benchmark problem. The proposed method provides an accurate and efficient approach to calculate the uncertainty of the top event in probabilistic safety assessment when the uncertainties of basic events are described with lognormal random variables.

• 대한안전경영과학회지
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• 제2권2호
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• pp.71-83
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• 2000

This paper presents accelerated life tests for Type I censoring data under probabilistic stresses. Probabilistic stress, $S_j$, is the random variable for stress influenced by test environments, test equipments, sampling devices and use conditions. The hazard rate, ,$theta_j$, is the random variable of environments and the function of probabilistic stress. Also it is assumed that the general stress distribution is uniform, the life distribution for the given hazard rate, $\theta$, is exponential and inverse power law model holds. In this paper, we obtained maximum likelihood estimators of model parameters and the mean life in use stress condition.