• Journal of Radiation Protection and Research
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• 제30권2호
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• pp.91-97
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• 2005

베이지안 기법은 객관적 자료 이외에 주관적 지식도 평가에 반영하는 특성으로 인해 최근 PRA에서 널리 사용되고 있다. 본 연구에서는 비파괴검사 장비 분실에 대한 방사선 위험도를 평가하기 위해 베이지안 기법을 활용하였다. U.S. NRC에서 제시한 선원분실 피폭 시나리오를 국내 실정에 맞게 재구성하였고 안전인자의 사고발생 확률에 국한하여 적용하였다. 사고발생 확률수정의 경우 Jeffreys사전분포를 사용한 결과가 모호사전분포를 사용한 결과보다 5 % 베이즈 하한치가 더 낮아서 방사선 사고와 같은 낮은 사고발생 확률을 가지는 시스템에 대한 위험도 평가에 적합하다. 위험도의 결과를 보면 일반인의 연간 예상되는 평균선량은 베이지안 기법이 고전적인 기법에 의거한 평가보다 높은 선량을 나타내는데 이는 수정된 안전인자 확률의 평균이 고전적 확률 참보다 높게 평가된 것에 기인한다. 국내의 경우 방사선 위험도 평가를 위한 자료구축이 미비한 바 베이지안 기법은 위험도 평가에 유용한 대안으로 활용할 수 있으며 이러한 연구는 위험도 정보-기반 규제에 기여할 것이다.

• 한국지진공학회논문집
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• 제25권3호
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• pp.145-152
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• 2021

KAERI has planned to carry out a series of dynamic tests using a shaking table and time-history analyses for a channel-type concrete shear wall to investigate its seismic performance because of the recently frequent occurrence of earthquakes in the south-eastern parts of Korea. The overall size of a test specimen is b×l×h =2500 mm×3500 mm×4500 mm, and it consists of three stories having slabs and walls with thicknesses of 140 mm and 150 mm, respectively. The system identification, FE model updating, and time-history analysis results for a test shear wall are presented herein. By applying the advanced system identification, so-called pLSCF, the improved modal parameters are extracted in the lower modes. Using three FE in-house packages, such as FEMtools, Ruaumoko, and VecTor4, the eigenanalyses are made for an initial FE model, resulting in consistency in eigenvalues. However, they exhibit relatively stiffer behavior, as much as 30 to 50% compared with those extracted from the test in the 1st and 2nd modes. The FE model updating is carried out to consider the 6-dofs spring stiffnesses at the wall base as major parameters by adopting a Bayesian type automatic updating algorithm to minimize the residuals in modal parameters. The updating results indicate that the highest sensitivity is apparent in the vertical translational springs at few locations ranging from 300 to 500% in variation. However, their changes seem to have no physical meaning because of the numerical values. Finally, using the updated FE model, the time-history responses are predicted by Ruaumoko at each floor where accelerometers are located. The accelerograms between test and analysis show an acceptable match in terms of maximum and minimum values. However, the magnitudes and patterns of floor response spectra seem somewhat different because of the slightly different input accelerograms and damping ratios involved.

• 한국콘텐츠학회논문지
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• 제20권6호
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• pp.1-8
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• 2020

빅데이터 분석에서 텍스트 데이터의 활용이 증가하고 있다. 따라서 텍스트 데이터의 분석 기법에 관한 많은 연구가 이루어지고 있다. 본 논문에서는 텍스트 데이터로부터 추출된 키워드 데이터의 분석을 위하여 공액사전분포 기반의 베이지안 학습 방법이 연구된다. 베이지안 통계학은 기존의 데이터에 새로운 데이터가 추가될 때마다 모수를 갱신하는 데이터 학습을 제공하기 때문에 시간에 따라 대용량의 데이터가 생성 및 추가되는 빅데이터 환경에서 효율적인 방법을 제공한다. 제안 방법의 성능과 적용 가능성을 보이기 위하여 실제 특허 빅데이터를 전처리하여 구축된 정형화된 키워드 데이터를 분석하는 사례연구를 수행한다.

• Earthquakes and Structures
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• 제12권6호
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• pp.653-663
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• 2017

A seismic margin assessment evaluates how much margin exists for the system under beyond design basis earthquake events. Specifically, the seismic margin for the entire system is evaluated by utilizing a systems analysis based on the sub-system and component seismic fragility data. Each seismic fragility curve is obtained by using empirical, experimental, and/or numerical simulation data. The systems analysis is generally performed by employing a fault tree analysis. However, the current practice has clear limitations in that it cannot deal with the uncertainties of basic components and accommodate the newly observed data. Therefore, in this paper, we present a Bayesian-based seismic margin assessment that is conducted using seismic fragility data and fault tree analysis including Bayesian inference. This proposed approach is first applied to the pooltype nuclear research reactor system for the quantitative evaluation of the seismic margin. The results show that the applied approach can allow updating by considering the newly available data/information at any level of the fault tree, and can identify critical scenarios modified due to new information. Also, given the seismic hazard information, this approach is further extended to the real-time risk evaluation. Thus, the proposed approach can finally be expected to solve the fundamental restrictions of the current method.

• Nuclear Engineering and Technology
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• 제54권4호
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• pp.1363-1373
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• 2022

The recent seismic events that occurred in South Korea have increased the interest in the re-evaluation of the seismic capacity of nuclear power plant (NPP) equipment, which is often conservatively estimated. To date, various approaches-including the Bayesian method proposed by the United States (US) Electric Power Research Institute -have been developed to quantify the seismic capacity of NPP equipment. Among these, the Bayesian approach has advantages in accounting for both prior knowledge and new information to update the probabilistic distribution of seismic capacity. However, data availability and region-specific issues exist in applying this Bayesian approach to Korean NPP equipment. Therefore, this paper proposes to construct an earthquake experience database by combining available earthquake records at Korean NPP sites and the general location of equipment within NPPs. Also, for the better representation of the seismic demand of Korean earthquake datasets, which have distinct seismic characteristics from those of the US at a high-frequency range, a broadband frequency range optimization is suggested. The proposed data construction and seismic demand optimization method for seismic capacity re-evaluation are demonstrated and tested on a 480 V motor control center of a South Korea NPP.

• Smart Structures and Systems
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• 제31권1호
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• pp.29-43
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• 2023

This study investigates the possibility of damage detection of a real bridge by means of a modal parameter-based finite element (FE) model update. Field moving vehicle experiments were conducted on an actual steel plate girder bridge. In the damage experiment, cracks were applied to the bridge to simulate damage states. A fast Bayesian FFT method was employed to identify and quantify uncertainties of the modal parameters then these modal parameters were used in the Bayesian model update. Material properties and boundary conditions are taken as uncertainties and updated in the model update process. Observations showed that although some differences existed in the results obtained from different model classes, the discrepancy between modal parameters of the FE model and those experimentally obtained was reduced after the model update process, and the updated parameters in the numerical model were indeed affected by the damage. The importance of boundary conditions in the model updating process is also observed. The capability of the MCMC model update method for application to the actual bridge structure is assessed, and the limitation of FE model update in damage detection of bridges using only modal parameters is observed.

• Structural Engineering and Mechanics
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• 제54권2호
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• pp.363-378
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• 2015

Estimation of geotechnical properties is an essential but challenging task since they are major components governing the safety and reliability of the entire structural system. However, due to time and budget constraints, reliable geotechnical properties estimation using traditional site characterization approach is difficult. In view of this, an alternative efficient and cost effective approach to address the overall uncertainty is necessary to facilitate an economical, safe and reliable geotechnical design. In this paper a probabilistic approach is proposed for real-time updating by incorporating new geotechnical information from the underlying project site. The updated model obtained from the proposed method is advantageous because it incorporates information from both existing database and the site of concern. An application using real data from a site in Hong Kong will be presented to demonstrate the proposed method.

• 한국전산구조공학회:학술대회논문집
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• 한국전산구조공학회 2007년도 정기 학술대회 논문집
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• pp.645-650
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• 2007

According to most studies, assessment of aging structure is trend to detect flaw size by sensor than using existing subjective evaluation by expert for objective evaluation. But Uncertainties existing in the sensor make difference between measured flaw size and actual flaw size, In this paper, Probability of Detection(POD) have been used to quantify the uncertainties and POD is updated by relationship measured flaw size and actual flaw size (Heasler, 1990), also we proposed probabilistic updating approach method to improve measurement accuracy(the difference of measured PDF and actual PDF) by using updated POD.

• 품질경영학회지
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• 제26권1호
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• pp.201-212
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• 1998

A methodology of the safety analysis on the fusion power plant is introduced. It starts with the understanding of the physics and engineering of the plant followed by the assessment of the tritium inventory and flow rate. We a, pp.y the probabilistic risk assessment. An event tree that explains the propagation of the accident is constructed and then it is translated in to an influence diagram, that is accident is constructed and then it is translated in to an influence diagram, that is statistically equivalent so far as the parameter updating is concerned. We follow the Bayesian a, pp.oach where model parameters are treated as random variables. We briefly discuss the parameter updating scheme, and finally develop the methodology to obtain the predictive distribution of time to next severe accident.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제10권8호
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• pp.3791-3805
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• 2016

The visual attention mechanism includes 2 attention models, the bottom-up (B-U) and the top-down (T-D), the physiology of which have not yet been accurately described. In this paper, the visual attention mechanism is regarded as a Bayesian fusion process, and a visual attention model based on particle filter is proposed. Under certain particular assumed conditions, a calculation formula of Bayesian posterior probability is deduced. The visual attention fusion process based on the particle filter is realized through importance sampling, particle weight updating, and resampling, and visual attention is finally determined by the particle distribution state. The test results of multigroup images show that the calculation result of this model has better subjective and objective effects than that of other models.