• 제목/요약/키워드: probabilistic method

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PLF(Probabilistic Load Flow)를 이용한 모선 전압 안전도 평가 (Security Assessment for Bus Voltages Using Probabilistic Load Flow)

  • 이승혁;정창호;김진오;김태균;추진부
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2003년도 추계학술대회 논문집 전력기술부문
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    • pp.28-30
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    • 2003
  • Probabilistic Load Flow(PLF) solution based on the method of moments is used for security assessment of bus voltages in power systems. Bus voltages, line currents, line admittances, generated real and reactive power, and bus loads are treated as complex random variables. These complex random variables are known in terms of probability density functions(PDF). Also, expressions for the convolutions of complex random variables in terms of moments and cumulants have been derived. Proposed PLF solution using the method of moments is fast, because the process of convolution of various complex random variables is performed in moment and cumulant domain. Therefore, the method is applied to security assessment of power systems in this paper. Finally, system operator also can be used information of security assessment to improve reliability of power systems.

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Hybrid parallel smooth particle hydrodynamic for probabilistic tsunami risk assessment and inland inundation

  • Sihombing, Fritz;Torbol, Marco
    • Smart Structures and Systems
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    • 제23권2호
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    • pp.185-194
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    • 2019
  • The probabilistic tsunami risk assessment of large coastal areas is challenging because the inland propagation of a tsunami wave requires an accurate numerical model that takes into account the interaction between the ground, the infrastructures, and the wave itself. Classic mesh-based methods face many challenges in the propagation of a tsunami wave inland due to their ever-moving boundary conditions. In alternative, mesh-less based methods can be used, but they require too much computational power in the far-field. This study proposes a hybrid approach. A mesh-based method propagates the tsunami wave from the far-field to the near-field, where the influence of the sea floor is negligible, and a mesh-less based method, smooth particle hydrodynamic, propagates the wave onto the coast and inland, and takes into account the wave structure interaction. Nowadays, this can be done because the advent of general purpose GPUs made mesh-less methods computationally affordable. The method is used to simulate the inland propagation of the 2004 Indian Ocean tsunami off the coast of Indonesia.

PROBABILISTIC MEASUREMENT OF RISK ASSOCIATED WITH INITIAL COST ESTIMATES

  • Seokyon Hwang
    • 국제학술발표논문집
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    • The 5th International Conference on Construction Engineering and Project Management
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    • pp.488-493
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    • 2013
  • Accurate initial cost estimates are essential to effective management of construction projects where many decisions are made in the course of project management by referencing the estimates. In practice, the initial estimates are frequently derived from historical actual cost data, for which standard distribution-based techniques are widely applied in the construction industry to account for risk associated with the estimates. This approach assumes the same probability distribution of estimate errors for any selected estimates. This assumption, however, is not always satisfied. In order to account for the probabilistic nature of estimate errors, an alternative method for measuring the risk associated with a selected initial estimate is developed by applying the Bayesian probability approach. An application example include demonstrates how the method is implemented. A hypothesis test is conducted to reveal the robustness of the Bayesian probability model. The method is envisioned to effectively complement cost estimating methods that are currently in use by providing benefits as follows: (1) it effectively accounts for the probabilistic nature of errors in estimates; (2) it is easy to implement by using historical estimates and actual costs that are readily available in most construction companies; and (3) it minimizes subjective judgment by using quantitative data only.

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확률파싱오토마타 모델 (A Model of Probabilistic Parsing Automata)

  • 이경옥
    • 정보과학회 논문지
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    • 제44권3호
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    • pp.239-245
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    • 2017
  • 확률문법은 자연어처리에서 사용되며, 확률문법에 대한 구문분석의 결과인 파스는 문법의 확률을 그대로 보존해야 한다. 대표적인 구문분석방법인 LL 파싱과 LR 파싱의 확률파싱 가능성을 살펴볼 때 LL 파싱은 문법의 확률정보를 그대로 유지하는 반면에 LR 파싱은 그렇지 않다. 확률문법과 확률파싱오토마톤과의 관계에 관한 기존 연구로 확률보존조건을 충족하는 오토마톤의 특성에 관한 연구는 진행된 바 있다. 그렇지만, 현재로서는 확률보존조건을 충족하는 오토마톤 생성모델에 관해서는 알려진 바가 없다. 본 논문에서는 단일상태파싱오토마타에 기반한 확률파싱오토마타 모델을 제안한다. 제안 모델로부터 생성되는 오토마톤은 확률보존조건을 보장하기에 별도의 확률파싱 가능 여부를 테스팅하는 단계가 불필요하고, 별도의 확률 함수를 정의하지 않아도 된다. 또한 매개인자를 적절하게 선택하여 효율적인 오토마톤의 생성이 가능하다.

확장된EIGC법에 의한 확업적 발전비 게산에 관한 연구 (A Study on the Probabilistic Production Cost Calculation by the Developed EIGC Method.)

  • 송길영;최재석;김용하
    • 대한전기학회논문지
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    • 제36권12호
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    • pp.839-847
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    • 1987
  • The probabilistic production cost is calculated by the Expected Incremental Generation Cost Curve(EIGC) method based on the multi-state and multi-block operating conditions. For this, A new algorithm for determining production cost by the EIGC and the generation availability curve (GAC) had been developed in order to realize better economic olad dispatch and better reliability for power system operation. The simpler method for determining the EIGC and the GAC is proposed for convenience and saving in computation time.

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Probabilistic penalized principal component analysis

  • Park, Chongsun;Wang, Morgan C.;Mo, Eun Bi
    • Communications for Statistical Applications and Methods
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    • 제24권2호
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    • pp.143-154
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    • 2017
  • A variable selection method based on probabilistic principal component analysis (PCA) using penalized likelihood method is proposed. The proposed method is a two-step variable reduction method. The first step is based on the probabilistic principal component idea to identify principle components. The penalty function is used to identify important variables in each component. We then build a model on the original data space instead of building on the rotated data space through latent variables (principal components) because the proposed method achieves the goal of dimension reduction through identifying important observed variables. Consequently, the proposed method is of more practical use. The proposed estimators perform as the oracle procedure and are root-n consistent with a proper choice of regularization parameters. The proposed method can be successfully applied to high-dimensional PCA problems with a relatively large portion of irrelevant variables included in the data set. It is straightforward to extend our likelihood method in handling problems with missing observations using EM algorithms. Further, it could be effectively applied in cases where some data vectors exhibit one or more missing values at random.

Direct fault-tree modeling of human failure event dependency in probabilistic safety assessment

  • Ji Suk Kim;Sang Hoon Han;Man Cheol Kim
    • Nuclear Engineering and Technology
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    • 제55권1호
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    • pp.119-130
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    • 2023
  • Among the various elements of probabilistic safety assessment (PSA), human failure events (HFEs) and their dependencies are major contributors to the quantification of risk of a nuclear power plant. Currently, the dependency among HFEs is reflected using a post-processing method in PSA, wherein several drawbacks, such as limited propagation of minimal cutsets through the fault tree and improper truncation of minimal cutsets exist. In this paper, we propose a method to model the HFE dependency directly in a fault tree using the if-then-else logic. The proposed method proved to be equivalent to the conventional post-processing method while addressing the drawbacks of the latter. We also developed a software tool to facilitate the implementation of the proposed method considering the need for modeling the dependency between multiple HFEs. We applied the proposed method to a specific case to demonstrate the drawbacks of the conventional post-processing method and the advantages of the proposed method. When applied appropriately under specific conditions, the direct fault-tree modeling of HFE dependency enhances the accuracy of the risk quantification and facilitates the analysis of minimal cutsets.

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.

Distance Based Dynamic Probabilistic Broadcasting in Ad Hoc Wireless Networks

  • Kim Jae-Soo;Kim Jeong-Hong
    • 한국멀티미디어학회논문지
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    • 제8권12호
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    • pp.1613-1622
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    • 2005
  • Broadcasting is fundamental and effective data dissemination mechanism for route discovery, address resolution, and many other network services in mobile ad hoc networks. Although many approaches for broadcasting have been proposed to minimize the number of retransmissions, none of them guarantee the best-suited bounds of retransmissions. Appropriate use of probabilistic method can lower the chance of contention and collision among neighboring nodes, so that it reduces the number of rebroadcasts. In this paper, we propose a probabilistic approach that dynamically adjusts the rebroadcasting probability according to the distance between the sender and the receiver. While the rebroadcast probabilities of a mobile node close to sender will be set lower, the rebroadcast probabilities of a mobile node far away from sender wi1l be set to higher, The rebroadcast probability of a node wi1l be set according to the distance from sender. We evaluate the performance of proposed approach by comparing it with flooding as well as a fixed probabilistic broadcast approach. Simulation results showed that the performance of proposed scheme outperforms by about $70\%$ than flooding scheme and outperforms by about $20\%$ than fixed probabilistic scheme.

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Probabilistic analysis for face stability of tunnels in Hoek-Brown media

  • Li, T.Z.;Yang, X.L.
    • Geomechanics and Engineering
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    • 제18권6호
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    • pp.595-603
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    • 2019
  • A modified model combining Kriging and Monte Carlo method (MC) is proposed for probabilistic estimation of tunnel face stability in this paper. In the model, a novel uniform design is adopted to train the Kriging, instead of the existing active learning function. It has advantage of avoiding addition of new training points iteratively, and greatly saves the computational time in model training. The kinematic approach of limit analysis is employed to define the deterministic computational model of face failure, in which the Hoek-Brown failure criterion is introduced to account for the nonlinear behaviors of rock mass. The trained Kriging is used as a surrogate model to perform MC with dramatic reduction of calls to actual limit state function. The parameters in Hoek-Brown failure criterion are considered as random variables in the analysis. The failure probability is estimated by direct MC to test the accuracy and efficiency of the proposed probabilistic model. The influences of uncertainty level, correlation relationship and distribution type of random variables are further discussed using the proposed approach. In summary, the probabilistic model is an accurate and economical alternative to perform probabilistic stability analysis of tunnel face excavated in spatially random Hoek- Brown media.