• 제목/요약/키워드: Probabilistic Models

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철근 콘크리트 부재강도의 확률적 특성 분석 (Statistical Analysis of Resistance of Rein forced Concrete Members)

  • 김상효;배규웅;박흥석
    • 한국콘크리트학회:학술대회논문집
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    • 한국콘크리트학회 1990년도 봄 학술발표회 논문집
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    • pp.90-95
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    • 1990
  • It is widely recognized that the strengths of reinforced concrete members have random characteristics due to the variability of the mechanical properties of concrete and steel, the dimensional error as well as incorrect placement of reinforcing bars. Statistical models of the variabilities of strengths of reinforced concrete members, therefore, need to be developed to evaluate the safety level implied in current practices. Based on the probabilistic models of basic factors affecting the R.C. member strengths, in this study, the probabilistic characteristics of member resistance have been studied through Monte Carlo simulation.

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효율적 영한기계번역을 위한 확률적 품사결정 (Probabilistic Part-Of-Speech Determination for Efficient English-Korean Machine Translation)

  • 김성동;김일민
    • 정보처리학회논문지B
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    • 제17B권6호
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    • pp.459-466
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    • 2010
  • 자연언어처리는 여러 가지 모호성 문제를 가지는데, 특히 영한기계번역은 번역 과정의 각 단계마다 해결해야 할 모호성 문제를 가진다. 본 논문에서는 실용적인 영한기계번역 시스템의 개발을 목적으로 영어 분석의 효율성을 높이기 위해 영어 단어의 품사 모호성 해소 문제에 초점을 두었다. 기계번역의 효율성 제고를 위해 영한기계번역 시스템에 통합하기 위한 품사결정 모듈은 빠른 시간에 정확한 품사결정을 하면서도 오류를 최소화 하여야 한다. 본 논문에서는 확률적 품사결정 방법을 제안하고 3가지 품사결정 확률 모델을 제시하였다. Penn Treebank 말뭉치로부터의 통계 정보를 이용하여 확률 모델을 구축하였으며 실험을 통해 제안한 품사결정 방법의 정확성과 품사결정에 의한 기계번역 시스템의 효율 향상 정도를 제시하였다.

Multistress Life Models of Epoxy Encapsulated Magnet wire under High Frequency Pulsating Voltage

  • Grzybowski, S.;Feilat, E.A.;Knight, P.
    • KIEE International Transactions on Electrophysics and Applications
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    • 제3C권1호
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    • pp.1-4
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    • 2003
  • This paper presents an attempt to develop probabilistic multistress life models to evaluate the lifetime characteristics of epoxy-encapsulated magnet wire with heavy build polyurethane enamel. A set of accelerated life tests were conducted over a wide range of pulsating voltages, temperatures, and frequencies. Samples of fine gauge twisted pairs of the encapsulated magnet wire were tested us-ing a pulse endurance dielectric test system. An electrical-thermal lifetime function was combined with the Weibull distribution of lifetimes. The parameters of the combined Weibull-electrical-thermal model were estimated using maximum likelihood estimation. Likewise, a generalized electrical-thermal-frequency life model was also developed. The parameters of this new model were estimated using multiple linear regression technique. It was found in this paper that lifetime estimates of the two proposed probabilistic multistress life models are good enough. This suggests the suitability of using the general electrical-thermal-frequency model to estimate the lifetime of the encapsulated magnet wire over a wide range of voltages, temperatures and pulsating frequencies.

Probabilistic evaluation of separation distance between two adjacent structures

  • Naeej, Mojtaba;Amiri, Javad Vaseghi;Jalali, Sayyed Ghasem
    • Structural Engineering and Mechanics
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    • 제67권5호
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    • pp.427-437
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    • 2018
  • Structural pounding is commonly observed phenomenon during major ground motion, which can cause both structural and architectural damages. To reduce the amount of damage from pounding, the best and effective way is to increase the separation distance. Generally, existing design procedures for determining the separation distance between adjacent buildings subjected to structural pounding are based on approximations of the buildings' peak relative displacement. These procedures are based on unknown safety levels. The aim of this research is to estimate probabilistic separation distance between adjacent structures by considering the variability in the system and uncertainties in the earthquakes characteristics through comprehensive numerical simulations. A large number of models were generated using a robust Monte-Carlo simulation. In total, 6.54 million time-history analyses were performed over the adopted models using an ensemble of 25 ground motions as seismic input within OpenSees software. The results show that a gap size of 50%, 70% and 100% of the considered design code for the structural periods in the range of 0.1-0.5 s, leads to have the probability of pounding about 41.5%, 18% and 5.8%, respectively. Finally, based on the results, two equations are developed for probabilistic determination of needed structural separation distance.

유전자 네트워크에서 확률적 그래프 모델을 이용한 정보 네트워크 추론 (Informatics Network Representation Using Probabilistic Graphical Models of Network Genetics)

  • 나상동;박동석;윤영지
    • 한국정보통신학회논문지
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    • 제10권8호
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    • pp.1386-1392
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    • 2006
  • 유전자 생물학 분야에서 여러 각도로 세포 간 네트워크를 입증하는 고 처리 정보공학 WWW에 응용하려는 수치학적인 표현 모델 분석 연구한다. 확률적 그래프 모델을 사용하여 데이터 네트워크로부터 생물학적 통찰력을 확률적 함수적으로 응용해 복잡한 세포 간 네트워크 보다 단순한 하부모델로 구성하여 유전자 베이스네트워크 논리를 유전자 표현 레벨로 나타낸다. 유전자 데이터로부터 확률적 그래프 모델들을 분석하여 유전자 표현 데이터를 정보 공학 네트워크 모델의 방법으로 확장 추론한다.

확률적 그래프 모델을 이용한 세포 간 정보 네트워크 추론 (Informatics Network Representation Between Cells Using Probabilistic Graphical Models)

  • 나상동;신현재;차월석
    • KSBB Journal
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    • 제21권4호
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    • pp.231-235
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    • 2006
  • 유전자 생물학 분야에서 적용가능 한 세포간 네트워크를 입증하는 고처리 정보공학에 응용하려는 수치학적인 표현 모델을 분석 연구한다. 확률적 그래프 모델을 사용하여 데이터 네트워크로부터 생물학적 통찰력을 확률적 함수적으로 응용해 복잡한 세포간 네트워크보다 단순한 하부모델로 구성하여 유전자 베이스네트워크 논리를 유전자 표현 레벨로 나타낸다. 유전자 데이터로부터 확률적 그래프 모델들을 분석하여 유전자 표현 데이터를 정보공학 네트워크 모델의 방법으로 확장 추론한다.

Bayesian demand model based seismic vulnerability assessment of a concrete girder bridge

  • Bayat, M.;Kia, M.;Soltangharaei, V.;Ahmadi, H.R.;Ziehl, P.
    • Advances in concrete construction
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    • 제9권4호
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    • pp.337-343
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    • 2020
  • In the present study, by employing fragility analysis, the seismic vulnerability of a concrete girder bridge, one of the most common existing structural bridge systems, has been performed. To this end, drift demand model as a fundamental ingredient of any probabilistic decision-making analyses is initially developed in terms of the two most common intensity measures, i.e., PGA and Sa (T1). Developing a probabilistic demand model requires a reliable database that is established in this paper by performing incremental dynamic analysis (IDA) under a set of 20 ground motion records. Next, by employing Bayesian statistical inference drift demand models are developed based on pre-collapse data obtained from IDA. Then, the accuracy and reasonability of the developed models are investigated by plotting diagnosis graphs. This graphical analysis demonstrates probabilistic demand model developed in terms of PGA is more reliable. Afterward, fragility curves according to PGA based-demand model are developed.

Probabilistic models for curvature ductility and moment redistribution of RC beams

  • Baji, Hassan;Ronagh, Hamid Reza
    • Computers and Concrete
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    • 제16권2호
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    • pp.191-207
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    • 2015
  • It is generally accepted that, in the interest of safety, it is essential to provide a minimum level of flexural ductility, which will allow energy dissipation and moment redistribution as required. If one wishes to be uniformly conservative across all of the design variables, curvature ductility and moment redistribution factor should be calculated using a probabilistic method, as is the case for other design parameters in reinforced concrete mechanics. In this study, simple expressions are derived for the evaluation of curvature ductility and moment redistribution factor, based on the concept of demand and capacity rotation. Probabilistic models are then derived for both the curvature ductility and the moment redistribution factor, by means of central limit theorem and through taking advantage of the specific behaviour of moment redistribution factor as a function of curvature ductility and plastic hinge length. The Monte Carlo Simulation (MCS) method is used to check and verify the results of the proposed method. Although some minor simplifications are made in the proposed method, there is a very good agreement between the MCS and the proposed method. The proposed method could be used in any future probabilistic evaluation of curvature ductility and moment redistribution factors.

Insights gained from applying negate-down during quantification for seismic probabilistic safety assessment

  • Kim, Ji Suk;Kim, Man Cheol
    • Nuclear Engineering and Technology
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    • 제54권8호
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    • pp.2933-2940
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    • 2022
  • Approximations such as the delete-term approximation, rare event approximation, and minimal cutset upper bound (MCUB) need to be prudently applied for the quantification of a seismic probabilistic safety assessment (PSA) model. Important characteristics of seismic PSA models indicate that preserving the success branches in a primary seismic event tree is necessary. Based on the authors' experience in modeling and quantifying plant-level seismic PSA models, the effects of applying negate-down to the success branches in primary seismic event trees on the quantification results are summarized along with the following three insights gained: (1) there are two competing effects on the MCUB-based quantification results: one tending to increase and the other tending to decrease; (2) the binary decision diagram does not always provide exact quantification results; and (3) it is identified when the exact results will be obtained, and which combination provides more conservative results compared to the others. Complicated interactions occur in Boolean variable manipulation, approximation, and the quantification of a seismic PSA model. The insights presented herein can assist PSA analysts to better understand the important theoretical principles associated with the quantification of seismic PSA models.

Generic and adaptive probabilistic safety assessment models: Precursor analysis and multi-purpose utilization

  • Ayoub, Ali;Kroger, Wolfgang;Sornette, Didier
    • Nuclear Engineering and Technology
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    • 제54권8호
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    • pp.2924-2932
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    • 2022
  • Motivated by learning from experience and exploiting existing knowledge in civil nuclear operations, we have developed in-house generic Probabilistic Safety Assessment (PSA) models for pressurized and boiling water reactors. The models are computationally light, handy, transparent, user-friendly, and easily adaptable to account for major plant-specific differences. They cover the common internal initiating events, frontline and support systems reliability and dependencies, human-factors, common-cause failures, and account for new factors typically overlooked in many PSAs. For quantification, the models use generic US reliability data, precursor analysis reports, the ETHZ Curated Nuclear Events Database, and experts' opinions. Moreover, uncertainties in the most influential basic events are addressed. The generated results show good agreement with assessments available in the literature with detailed PSAs. We envision the models as an unbiased framework to measure nuclear operational risk with the same "ruler", and hence support inter-plant risk comparisons that are usually not possible due to differences in plant-specific PSA assumptions and scopes. The models can be used for initial risk screening, order-of-magnitude precursor analysis, and other research/pedagogic applications especially when no plant-specific PSAs are available. Finally, we are using the generic models for large-scale precursor analysis that will generate big picture trends, lessons, and insights.