• 제목/요약/키워드: Probabilistic Evaluation

검색결과 554건 처리시간 0.028초

확률론적 공급신뢰도 평가를 위한 전압레벨별 데이터베이스 구축방안 (Construction of Database for Reliability Evaluation of the Large Power System)

  • 문승필;신태우;장병훈;전동훈;곽희섭;한경남;최재석
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2006년도 제37회 하계학술대회 논문집 A
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    • pp.74-75
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    • 2006
  • The reliability evaluation methods for the bulk power system habe been studied by several electric utilities. The evaluation methods based on the probability theory and the computer packages are being developed or already practicalized. But without correct probabilistic data, accurate result couldn't be expected. In this point, the construction of database is needed. Some of probabilistic data for evaluation of bulk power system are shown in this paper.

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확률기반 해상위기평가에서 실시간 민감도를 이용한 위기수준의 단계 구분 수 결정에 관한 연구 (Determining the Number of Risk Level Using Real-time Sensitivities in the Probabilistic Maritime Risk Evaluation)

  • 강상근
    • 해양환경안전학회지
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    • 제20권6호
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    • pp.685-691
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    • 2014
  • 해상에서 발생하는 위기의 확률적인 평가결과는 확률(P=0.0~1.0)로 나타난다. 이러한 확률적인 위기평가결과는 위험한 정도를 쉽게 알기 위하여 일반적으로 평가의 기준이 되는 위기허용수준(Risk Acceptance Criteria, RAC)을 이용하여 지수(index)로 나타낸다. 현재 RAC은 3단계, 5단계, 7단계 등으로 구분하는데, 구분한 단계 수가 위기평가에 적합한지를 평가할 필요가 있음에도 불구하고 관련 연구가 전무한 실정이다. 본 연구에서는 RAC의 단계 구분 수에 따른 민감도(Sensitivity)와 민감도의 분포특성을 이용하여 최적의 RAC 구분 단계 수를 정할 수 있는 평가기법을 제안하였다. 사전 연구결과로부터 획득한 확률적인 위기평가 데이터에 대해서 제안한 기법을 적용한 결과, 민감도가 10배 이내로 형성되는 최적의 RAC 구분 단계 수를 결정할 수 있었고, 이를 통해서 제안한 방법의 유효성을 확인하였다.

폴리아세탈 소재의 확률론적 변형률-수명선도 평가 (An Evaluation of Probabilistic Strain-Life Curve in Polyacetal)

  • 장천수;김철수;박범규;김정규
    • 대한기계학회논문집A
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    • 제30권11호
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    • pp.1417-1424
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    • 2006
  • In order to evaluate variation of fatigue life of mechanical components including engineering plastics, it is important to estimate probabilistic strain-life curves to accurately define the variation of fatigue characteristics. This paper intends to provide new assessment of P-$\varepsilon$-N (probabilistic strain-life curves) for considering the variation of fatigue characteristics in polyacetal. The fatigue strain controlled tests were conducted under constant 50% humidity and room temperature condition by a universal testing machine at strain ratio, R=0. A practical procedure is introduced to evaluate probabilistic strain-life curves. Three probabilistic distributions were used for generating P-$\varepsilon$-N curves such as normal, 2-parameter and 3-parameter Weibull. In this study, 3-parameter Weibull distribution was found to be most appropriate among assumed distributions when the probability distributions of the fatigue characteristic were examined using chi-square and Kolmogorov-Smirnov test. The more appropriate P-$\varepsilon$-N curves for these materials are generated by the proposed method considering 3-parameter Weibull distribution.

Probabilistic analysis of gust factors and turbulence intensities of measured tropical cyclones

  • Tianyou Tao;Zao Jin;Hao Wang
    • Wind and Structures
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    • 제38권4호
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    • pp.309-323
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    • 2024
  • The gust factor and turbulence intensity are two crucial parameters that characterize the properties of turbulence. In tropical cyclones (TCs), these parameters exhibit significant variability, yet there is a lack of established formulas to account for their probabilistic characteristics with consideration of their inherent connection. On this condition, a probabilistic analysis of gust factors and turbulence intensities of TCs is conducted based on fourteen sets of wind data collected at the Sutong Cable-stayed Bridge site. Initially, the turbulence intensities and gust factors of recorded data are computed, followed by an analysis of their probability densities across different ranges categorized by mean wind speed. The Gaussian, lognormal, and generalized extreme value (GEV) distributions are employed to fit the measured probability densities, with subsequent evaluation of their effectiveness. The Gumbel distribution, which is a specific instance of the GEV distribution, has been identified as an optimal choice for probabilistic characterizations of turbulence intensity and gust factor in TCs. The corresponding empirical models are then established through curve fitting. By utilizing the Gumbel distribution as a template, the nexus between the probability density functions of turbulence intensity and gust factor is built, leading to the development of a generalized probabilistic model that statistically describe turbulence intensity and gust factor in TCs. Finally, these empirical models are validated using measured data and compared with suggestions recommended by specifications.

CWR 궤도의 좌굴 안정성에 대한 결정론적 해석과 확률론적 해석 비교 (A Comparative Study between the Deterministic and Probabilistic Approach Analysis on Buckling Stability of CWR Tracks)

  • 배현웅;최진유;신정상;김종중;임남형
    • 한국철도학회:학술대회논문집
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    • 한국철도학회 2011년도 춘계학술대회 논문집
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    • pp.988-992
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    • 2011
  • The buckling characteristics of the continuous welded rail track(CWR) is uncertainly varied by many influence factors, such as rail temperature, operating conditions of a train and maintenance of the track etc. Therefore, applying the probabilistic approach method is essential to rationally consider uncertainty and randomness of the various parameters that affect the track buckling. In this study, the probabilistic approach analysis was carried out and the results were compared with the deterministic approach using the buckling probability evaluation system of CWR tracks developed by our research team. From the comparison, it was identified that a probabilistic approach can quantitatively assess the reliability of the CWR tracks based on failure probability and can be used as a tool for decision making in track design, maintenance and operating etc.

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지반변동성을 고려한 액상화 진동전단응력비의 확률론적 해석 (Probabilistic Analysis of Liquefaction Cyclic Stress Ratio Considering Soil Variability)

  • 허준
    • 한국농공학회논문집
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    • 제60권2호
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    • pp.95-101
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    • 2018
  • The objective of this study is to evaluate the liquefaction cyclic shear stress ratio considering the soil uncertainty. In this study, the probabilistic ground response analysis and the cyclic shear stress ratio analysis for the liquefaction potential evaluation are performed considering the soil variability. The statistical properties of input ground parameters were analyzed to investigate the parameters affecting the seismic response analysis. The Probabilistic analysis was carried out by Monte Carlo Simulation method. The ground response analysis was performed considering the soil variability and the probability distribution characteristics of the ground acceleration. The probability distribution of the peak ground acceleration by seismic characteristics was presented. The differences of liquefaction shear stress ratio results according to soil variability were compared and analyzed. The maximum acceleration of the ground by the deterministic method was analyzed to be overestimation of the ground amplification phenomenon. Also, the shear stress ratio was overestimated.

우주 발사체 추진기관 시스템에 대한 확률적 위험 분석 적용 (Application of Probabilistic Risk Assessment to Space Launch Vehicle Propulsion System)

  • 조상연;신명호;김용욱;오승협
    • 한국추진공학회:학술대회논문집
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    • 한국추진공학회 2006년도 제27회 추계학술대회논문집
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    • pp.71-74
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    • 2006
  • 본 논문은 미국의 우주개발과 함께 고안되어 여러 산업에 걸쳐 적용된 바 있는 확률적 위험 분석(probabilistic Risk Assessment; PRA) 기법의 역사와 내용을 소개하고 현재 항공우주연구연이 개발하고 있는 소형위성발사체(KSLV-I)의 추진기관에 대하여 그 흐름대로 적용하여 실제 기술적 위험 관리와 신뢰도 분석에 적용 가능함을 확인하고 한다.

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확률론적 파괴역학 수법의 적용성 검토 (Application of Probabilistic Fracture Mechanics Methodology)

  • 이준성;곽상록;김영진
    • 한국정밀공학회:학술대회논문집
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    • 한국정밀공학회 2001년도 춘계학술대회 논문집
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    • pp.667-670
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    • 2001
  • For major structural components periodic inspections and integrity assessments are needed for the safety. However, many flaws are undetectable because sampling inspection is carried out during in-service inspection. Probabilistic integrity assessment is applied to take into consideration of uncertainty and variance of input parameters arise due to material properties and undetectable cracks. This paper describes a Probabilistic Fracture Mechanics(PEM) analysis based on the Monte Carlo(MC) algorithms. Taking a number of sampling data of probabilistic variables such as fracture toughness value, crack depth and aspect ratio of an initial surface crack, a MC simulation of failure judgement of samples is performed. For the verification of this analysis, a comparison study of th PFM analysis using a commercial code, mathematical method is carried out and a good agreement was observed between those results.

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몬테카를로 시뮬레이션에 의한 선박용 프로펠러재의 피로수명 확률분포 평가 (Evaluation for Probabilistic Distributions of Fatigue Life of Marine Propeller Materials by using a Monte Carlo Simulation)

  • 윤한용;장건위
    • 대한기계학회논문집A
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    • 제32권12호
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    • pp.1055-1062
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    • 2008
  • Engineering materials have been studied and developed remarkably for a long time. But, few reports about marine propeller materials are presented. Recently, some researchers have studied the material strength of marine propellers. However, studies on parametric sensitivity and probabilistic distribution of fatigue life of propeller materials have not been made yet. In this study, a method to predict the probabilistic distributions of fatigue life of propeller materials is presented, and the influence of several parameters on the life distribution is discussed.

압력관의 확률론적평가에 타당한 파손평가선도 작성에 관한 연구 (A Study on FAD Development for Probabilistic Pressure Tube Integrity Assessment)

  • 곽상록;왕종배;최영환;박윤원
    • 대한기계학회:학술대회논문집
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    • 대한기계학회 2003년도 추계학술대회
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    • pp.1211-1215
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    • 2003
  • Pressure tubes are major component of nuclear reactor, but only selected samples are periodically examined due to numerous numbers of tubes. Current in-service inspection result show there is high probability of flaw existence at un-inspected pressure tube. Probabilistic analysis is applied in this study for the integrity assessment of un-inspected pressure tube. But all the current integrity evaluations procedures are based on conventional deterministic approaches. So many integrity evaluation parameters are not directly apply to probabilistic analysis. As a result of this study failure assessment diagram are proposed based on test data.

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