• 제목/요약/키워드: epistemic uncertainty

검색결과 35건 처리시간 0.025초

최소생애주기비용을 위한 PSC보 보강의 최적설계 (Optimal Design of the PSC Beam Reinforcement for Minimum Life-Cycle Cost)

  • 방명식;한성호
    • 한국안전학회지
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    • 제23권5호
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    • pp.125-130
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    • 2008
  • PSC보의 보강 시에 안전도분석을 위한 신뢰성해석과 생애주기비용을 최소화하기 위만 최적설계를 실시하였다. 신뢰성해석은 현재 공용중인 표준단면을 변형시키면서 실시하며 자연적 불확실성과 인위적 불확실성을 고려하였다. 자연적(내재적) 불확실성을 고려하여 최소생애주기비용을 구한 후에, 인위적 불확실성을 최대 90%의 분산까지 고려하여 재해석을 실시하였다. 보강방법에 대한 신뢰성해석과 최소생애주기비용해석은 보강방법을 결정하는데 매우 합리적인 기준을 제시하였다.

TREATING UNCERTAINTIES IN A NUCLEAR SEISMIC PROBABILISTIC RISK ASSESSMENT BY MEANS OF THE DEMPSTER-SHAFER THEORY OF EVIDENCE

  • Lo, Chung-Kung;Pedroni, N.;Zio, E.
    • Nuclear Engineering and Technology
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    • 제46권1호
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    • pp.11-26
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    • 2014
  • The analyses carried out within the Seismic Probabilistic Risk Assessments (SPRAs) of Nuclear Power Plants (NPPs) are affected by significant aleatory and epistemic uncertainties. These uncertainties have to be represented and quantified coherently with the data, information and knowledge available, to provide reasonable assurance that related decisions can be taken robustly and with confidence. The amount of data, information and knowledge available for seismic risk assessment is typically limited, so that the analysis must strongly rely on expert judgments. In this paper, a Dempster-Shafer Theory (DST) framework for handling uncertainties in NPP SPRAs is proposed and applied to an example case study. The main contributions of this paper are two: (i) applying the complete DST framework to SPRA models, showing how to build the Dempster-Shafer structures of the uncertainty parameters based on industry generic data, and (ii) embedding Bayesian updating based on plant specific data into the framework. The results of the application to a case study show that the approach is feasible and effective in (i) describing and jointly propagating aleatory and epistemic uncertainties in SPRA models and (ii) providing 'conservative' bounds on the safety quantities of interest (i.e. Core Damage Frequency, CDF) that reflect the (limited) state of knowledge of the experts about the system of interest.

Risk assessment of steel and steel-concrete composite 3D buildings considering sources of uncertainty

  • Lagaros, Nikos D.
    • Earthquakes and Structures
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    • 제6권1호
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    • pp.19-43
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    • 2014
  • A risk assessment framework for evaluating building structures is implemented in this study. This framework allows considering sources of uncertainty both on structural capacity and seismic demand. In particular randomness on seismic load, incident angle, material properties, floor mass and structural damping are considered; in addition the choice of fibre modelling versus plastic hinge model is also considered as a source of uncertainty. The main objective of this work is to study the contribution of these sources of uncertainty on the fragilities of steel and steel-reinforced concrete composite 3D building structures. The fragility curves are expressed in the form of a two-parameter lognormal distribution where vertical statistics in conjunction with metaheuristic optimization are implemented for calculating the two parameters.

An improvement on fuzzy seismic fragility analysis using gene expression programming

  • Ebrahimi, Elaheh;Abdollahzadeh, Gholamreza;Jahani, Ehsan
    • Structural Engineering and Mechanics
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    • 제83권5호
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    • pp.577-591
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    • 2022
  • This paper develops a comparatively time-efficient methodology for performing seismic fragility analysis of the reinforced concrete (RC) buildings in the presence of uncertainty sources. It aims to appraise the effectiveness of any variation in the material's mechanical properties as epistemic uncertainty, and the record-to-record variation as aleatory uncertainty in structural response. In this respect, the fuzzy set theory, a well-known 𝛼-cut approach, and the Genetic Algorithm (GA) assess the median of collapse fragility curves as a fuzzy response. GA is requisite for searching the maxima and minima of the objective function (median fragility herein) in each membership degree, 𝛼. As this is a complicated and time-consuming process, the authors propose utilizing the Gene Expression Programming-based (GEP-based) equation for reducing the computational analysis time of the case study building significantly. The results indicate that the proposed structural analysis algorithm on the derived GEP model is able to compute the fuzzy median fragility about 33.3% faster, with errors less than 1%.

크리깅 기반 차원감소법을 이용한 베이지안 신뢰도 해석 (Bayesian Reliability Analysis Using Kriging Dimension Reduction Method(KDRM))

  • 안다운;최주호;원준호
    • 한국전산구조공학회논문집
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    • 제21권3호
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    • pp.275-280
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    • 2008
  • 신뢰성 기반 형상 최적화(RBDO)글 위한 기술은 한정된 정보로 인한 인식론적 불확실성을 다룰 수 있는 베이지안 접근에 근거하여 발달된다. 최근까지, 전통적인 RBDO는 측정 데이터가 무한히 많아서 확실한 확률정보를 알고 있다는 가정 하에 실행되었다. 하지만 실제로는, 부족한 데이터로 인해 기존의 RBDO 방법의 유용성을 떨어뜨린다. 본 연구에서는, 확률정보의 불확실성을 인식하고, 따라서 산포를 갖게 되는 시스템 신뢰도의 확률 분포에서의 신뢰수준의 하한 값을 고려하기 위해 '베이지안 신뢰성'이 소개된다. 이런 경우, 베이지안 신뢰성 해석은 기존 신뢰도 해석의 이중 해석을 요구하게 된다. 크리깅 기반 차원 감소 방법(KDRM)은 신뢰도 해석을 위한 새로운 효율적인 방법으로써 사용되며, 제시된 방법은 몇 가지 수치예제를 사용하여 설명된다.

베이지안 접근법을 이용한 입력변수 및 근사모델 불확실성 하에 서의 신뢰성 분석 (Reliability Analysis Under Input Variable and Metamodel Uncertainty Using Simulation Method Based on Bayesian Approach)

  • 안다운;원준호;김은정;최주호
    • 대한기계학회논문집A
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    • 제33권10호
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    • pp.1163-1170
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    • 2009
  • Reliability analysis is of great importance in the advanced product design, which is to evaluate reliability due to the associated uncertainties. There are three types of uncertainties: the first is the aleatory uncertainty which is related with inherent physical randomness that is completely described by a suitable probability model. The second is the epistemic uncertainty, which results from the lack of knowledge due to the insufficient data. These two uncertainties are encountered in the input variables such as dimensional tolerances, material properties and loading conditions. The third is the metamodel uncertainty which arises from the approximation of the response function. In this study, an integrated method for the reliability analysis is proposed that can address all these uncertainties in a single Bayesian framework. Markov Chain Monte Carlo (MCMC) method is employed to facilitate the simulation of the posterior distribution. Mathematical and engineering examples are used to demonstrate the proposed method.

소음에 대한 초등 예비교사들의 탐구에서 나타나는 1차 데이터와 2차 데이터 활용의 인식적 특징 비교 - 과학탐구 보고서 사례를 중심으로 - (Comparison of Epistemic Characteristics of Using Primary and Secondary Data in Inquiries about Noise Conducted by Elementary School Preservice Teachers: Focusing on the Cases of Science Inquiry Reports)

  • 장진아;나지연
    • 한국초등과학교육학회지:초등과학교육
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    • 제43권1호
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    • pp.81-94
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    • 2024
  • 이 연구에서는 생활 속 위험 문제 중 하나인 '소음'에 대해 예비교사들이 수행한 과학탐구 사례를 중심으로 서로 다른 유형의 데이터 활용에서 나타나는 인식적 특징을 탐색하고 비교하였다. 이를 위해, 소음에 대한 탐구 보고서를 수집하고, 탐구 보고서에서 1차 데이터와 2차 데이터가 어떻게 과학탐구에 활용되는지, 데이터의 유형에 따라 탐구 설계, 자료 수집 및 분석 과정이 어떻게 달라지는지를 분석하였다. 연구 결과, 센서 기반의 1차 데이터는 핵심 현상을 측정하고 관찰하는 주체가 탐구자 자신이지만, 2차 데이터는 공공 기관에서 이미 측정 대상과 방법을 결정하여 데이터로 제시하였기 때문에 예비교사들은 공공 데이터의 특징을 먼저 조사하고 탐구 목적에 맞게 선별적으로 활용하였다. 이러한 차이로 인해 탐구 과정에서 요구되는 인식적 고려 사항과 방식이 서로 달랐다. 끝으로 이러한 연구 결과가 과학탐구 교수학습 및 탐구 지도를 위한 교사교육, 그리고 변동성과 불확실성이 극대화될 VUCA 시대를 대비한 위험 대응 역량 교육의 측면에서 갖는 교육적 시사점을 논의하였다.

생애주기비용의 최소화에 의한 현수교의 목표안전수준 결정방법 (Decision Method on Target Safety Level in Suspension Bridges by Minimization of Life Cycle Cost)

  • 방명석
    • 한국안전학회지
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    • 제24권2호
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    • pp.62-68
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    • 2009
  • Life Cycle Cost(LCC) is adopted to decide the target of safety level in designing suspension bridges. The LCC are evaluated considering two types of uncertainty; aleatory and epistemic. The nine alternative designs of suspension bridge are simulated to decide the safety level which can minimize the LCC. The LCC is calculated through the probability of failure and safety index including the uncertainty. This method results in the useful tool deciding the optimum safety level with minimal LCC as the main design factor.

RISK-INFORMED REGULATION: HANDLING UNCERTAINTY FOR A RATIONAL MANAGEMENT OF SAFETY

  • Zio, Enrico
    • Nuclear Engineering and Technology
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    • 제40권5호
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    • pp.327-348
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    • 2008
  • A risk-informed regulatory approach implies that risk insights be used as supplement of deterministic information for safety decision-making purposes. In this view, the use of risk assessment techniques is expected to lead to improved safety and a more rational allocation of the limited resources available. On the other hand, it is recognized that uncertainties affect both the deterministic safety analyses and the risk assessments. In order for the risk-informed decision making process to be effective, the adequate representation and treatment of such uncertainties is mandatory. In this paper, the risk-informed regulatory framework is considered under the focus of the uncertainty issue. Traditionally, probability theory has provided the language and mathematics for the representation and treatment of uncertainty. More recently, other mathematical structures have been introduced. In particular, the Dempster-Shafer theory of evidence is here illustrated as a generalized framework encompassing probability theory and possibility theory. The special case of probability theory is only addressed as term of comparison, given that it is a well known subject. On the other hand, the special case of possibility theory is amply illustrated. An example of the combination of probability and possibility for treating the uncertainty in the parameters of an event tree is illustrated.

A Systems Engineering Approach for Uncertainty Analysis of a Station Blackout Scenario

  • de Sousa, J. Ricardo Tavares;Diab, Aya
    • 시스템엔지니어링학술지
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    • 제15권1호
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    • pp.51-59
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    • 2019
  • After Fukushima Dai-ichi NPP accident, the need for implementation of diverse and flexible coping strategies (FLEX) became evident. However, to ensure the effectiveness of the safety strategy, it is essential to quantify the uncertainties associated with the station blackout (SBO) scenario as well as the operator actions. In this paper, a systems engineering approach for uncertainty analysis (UA) of a SBO scenario in advanced pressurized water reactor is performed. MARS-KS is used as a best estimate thermal-hydraulic code and is loosely-coupled with Dakota software which is employed to develop the uncertainty quantification framework. Furthermore, the systems engineering approach is adopted to identify the requirements, functions and physical architecture, and to develop the verification and validation plan. For the preliminary analysis, 13 uncertainty parameters are propagated through the model to evaluate the stability and convergence of the framework. The developed framework will ultimately be used to quantify the aleatory and epistemic uncertainties associated with an extended SBO accident scenario and assess the coping capability of APR1400 and the effectiveness of the implemented FLEX strategies.