• 제목/요약/키워드: Randomness

검색결과 448건 처리시간 0.03초

확률유한요소법에 의한 철근 콘크리트 프레임의 응답변화도 (Response Variability of Reinforced Concrete Frame by the Stochastic Finite Element Method)

  • 정영수
    • 전산구조공학
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    • 제7권1호
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    • pp.125-134
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    • 1994
  • Response variability of reinforced concrete frame subjected to material property randomness has been evaluated with the aid of the finite element method. The spatial variation of Young's modulus is assumed to be a two-dimensional homogeneous stochastic process. Young's Modulus of concrete material has been investigated based on the uiaxial strength of concrete cylinder. Direct Monte Carlo simulation method is used to investigate the response of reinforced concrete frame due to the variation of Young's modulus with the Neumann expansion method and the pertubation method. The results by three analytic methods are compared with those by deterministic finite element analysis. These stochastic technique may be an efficient tool for evaluating the structural safety and reliability of reinforced concrete structures.

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교량의 지진거동에 미치는 영향인자에 관한 연구 (A Study of influence factors on the bridge seismic behavior)

  • 최종만;국승규;김준범;정동원
    • 한국지진공학회:학술대회논문집
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    • 한국지진공학회 2005년도 학술발표회 논문집
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    • pp.372-379
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    • 2005
  • The earthquake resistant design concept allows the nonlinear behavior of structures under the design earthquake. Therefore the response spectrum method provided in most codes introduces the response modification factors to consider the nonlinear behavior in the design process. For bridges, the response modification factors are given according to the ductility as well as the redundancy of piers. In this study, among influence factors on the nonlinear seismic behavior, the randomness of artificial accelerograms simulated with different durations, the pier ductility represented by the inelastic behavior characteristic curve and the regularity represented by pier heights are selected. The influence of such factor on the seismic behavior is investigated by comparing response modification factors calculated with the nonlinear time step analysis.

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Probabilistic stability analysis of underground structure using stochastic finite element method

  • Na, Sang-Min;Moon, Hyun-Koo
    • 한국지구물리탐사학회:학술대회논문집
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    • 한국지구물리탐사학회 2003년도 Proceedings of the international symposium on the fusion technology
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    • pp.192-197
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    • 2003
  • It can be said that rock mass properties are characterized not by a mean value but by values with variation due to its characteristic uncertainty. This characteristic is one of the most important parts for the design of underground structures, but yet to be fully examined. Stochastic finite element method (SFEM) has been developed in order to take the randomness of structural systems into account. Using SFEM, the response variability of structural system can be obtained and it leads probabilistic stability of structure to be analyzed. In this study, displacements response variability of circular opening with hydrostatic stress field are analyzed in terms of rock mass properties having a certain mean and a standard deviation using the SFEM. The analyzed response variability shows that the necessity of probabilistic stability analysis of underground structures using reliable mean value and standard deviation of deformation modulus.

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언어 텍스트에 나타나는 벤포드 법칙: 원리와 응용 (Benford's Law in Linguistic Texts: Its Principle and Applications)

  • 홍정하
    • 한국언어정보학회지:언어와정보
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    • 제14권1호
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    • pp.145-163
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    • 2010
  • This paper aims to propose that Benford's Law, non-uniform distribution of the leading digits in lists of numbers from many real-life sources, also appears in linguistic texts. The first digits in the frequency lists of morphemes from Sejong Morphologically Analyzed Corpora represent non-uniform distribution following Benford's Law, but showing complexity of numerical sources from complex systems like earthquakes. Benford's Law in texts is a principle reflecting regular distribution of low-frequency linguistic types, called LNRE(large number of rare events), and governing texts, corpora, or sample texts relatively independent of text sizes and the number of types. Although texts share a similar distribution pattern by Benford's Law, we can investigate non-uniform distribution slightly varied from text to text that provides useful applications to evaluate randomness of texts distribution focused on low-frequency types.

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Reliability Evaluation of a Distribution System with wind Turbine Generators Based on the Switch-section Partitioning Method

  • Wu, Hongbin;Guo, Jinjin;Ding, Ming
    • Journal of Electrical Engineering and Technology
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    • 제11권3호
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    • pp.575-584
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    • 2016
  • Considering the randomness and uncertainty of wind power, a reliability model of WTGs is established based on the combination of the Weibull distribution and the Markov chain. To analyze the failure mode quickly, we use the switch-section partitioning method. After defining the first-level load zone node, we can obtain the supply power sets of the first-level load zone nodes with each WTG. Based on the supply sets, we propose the dynamic division strategy of island operation. By adopting the fault analysis method with the attributes defined in the switch-section, we evaluate the reliability of the distribution network with WTGs using a sequential Monte Carlo simulation method. Finally, using the IEEE RBTS Bus6 test system, we demonstrate the efficacy of the proposed model and method by comparing different schemes to access the WTGs.

피크 부하의 불확실성을 고려한 전력계통의 신뢰도 산출 (Reliability Evaluation considering Fuzzy-based Uncertainty of Peak Load Forecast)

  • 김동민;김진오
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2008년도 제39회 하계학술대회
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    • pp.111-112
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    • 2008
  • Although two types of uncertainty such as randomness and fuzziness simultaneously exist in power systems, yet they have been treated as distinct fields to evaluate the power system reliability. Thus, this paper presents a reliability assessment method based on a combined concept of fuzzy and probability. To reflect the two-fold uncertainty, a modified load duration curve(MLDC) is proposed using the probability distribution of historical load data in which a fuzzy model for the peak load forecast is embedded. IEEE RTS system was used to demonstrate the usefulness and applicability of the proposed method, and the reliability indices were obtained using the proposed MLDC. The results show a wider insight into impact of load fuzziness on uncertainties of reliability indices for power systems.

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품질경영시대의 유연성을 갖는 생산시스템의 성능분석 및 평가 (Performance Analysis and Evaluation for Flexibility of Manufacturing Systems in QM era)

  • 이승현;유왕진
    • 품질경영학회지
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    • 제27권2호
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    • pp.251-262
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    • 1999
  • In the automated manufacturing systems, the problem regarding how to make production activities flexible is even more important and critical than that regarding how to product large quantities, and the more flexible, if possible, the manufacturing system is, the more competitiveness and profitable factors it gets. This research, therefore, concentrated on establishing the flexibility and evaluating performance on the manufacturing system, operational flexibility is considered because of enabling the manufacturing system to get both the improvement of production rate and the adaptive ability of environment changes. For it, we used the analytical tool, GSPNs, which is a kind of timed Petri-Nets. GSPNs is competent enough to consider practical situations just like operation priorities, machine failure, randomness, concurrency and so on. Through the GSPNs analysis, it is confirmed that in the manufacturing system with operational flexibility is compatible with the traditional performances such as production rate or mean waiting time.

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Statistical and Entropy Based Human Motion Analysis

  • Lee, Chin-Poo;Woon, Wei-Lee;Lim, Kian-Ming
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제4권6호
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    • pp.1194-1208
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    • 2010
  • As visual surveillance systems gain wider usage in a variety of fields, it is important that they are capable of interpreting scenes automatically, also known as "human motion analysis" (HMA). However, existing HMA methods are too domain specific and computationally expensive. This paper proposes a general purpose HMA method that is based on the idea that human beings tend to exhibit erratic motion patterns during abnormal situations. Limb movements are characterized using the statistics of angular and linear displacements. In addition, the method is enhanced via the use of the entropy of the Fourier spectrum to measure the randomness of subject's motions. Various experiments have been conducted and the results indicate that the proposed method has very high classification accuracy in identifying anomalous behavior.

The hybrid uncertain neural network method for mechanical reliability analysis

  • Peng, Wensheng;Zhang, Jianguo;You, Lingfei
    • International Journal of Aeronautical and Space Sciences
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    • 제16권4호
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    • pp.510-519
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    • 2015
  • Concerning the issue of high-dimensions, hybrid uncertainties of randomness and intervals including implicit and highly nonlinear limit state function, reliability analysis based on the hybrid uncertainty reliability mode combining with back propagation neural network (HU-BP neural network) is proposed in this paper. Random variables and interval variables are as input layer of the neural network, after the training and approximation of the neural network, the response variables are obtained through the output layer. Reliability index is calculated by solving the optimization model of the most probable point (MPP) searching in the limit state band. Two numerical cases are used to demonstrate the method proposed in this paper, and finally the method is employed to solving an engineering problem of the aerospace friction plate. For this high nonlinear, small failure probability problem with interval variables, this method could achieve a good analysis result.

Crowd escape event detection based on Direction-Collectiveness Model

  • Wang, Mengdi;Chang, Faliang;Zhang, Youmei
    • KSII Transactions on Internet and Information Systems (TIIS)
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    • 제12권9호
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    • pp.4355-4374
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    • 2018
  • Crowd escape event detection has become one of the hottest problems in intelligent surveillance filed. When the 'escape event' occurs, pedestrians will escape in a disordered way with different velocities and directions. Based on these characteristics, this paper proposes a Direction-Collectiveness Model to detect escape event in crowd scenes. First, we extract a set of trajectories from video sequences by using generalized Kanade-Lucas-Tomasi key point tracker (gKLT). Second, a Direction-Collectiveness Model is built based on the randomness of velocity and orientation calculated from the trajectories to express the movement of the crowd. This model can describe the movement of the crowd adequately. To obtain a generalized crowd escape event detector, we adopt an adaptive threshold according to the Direction-Collectiveness index. Experiments conducted on two widely used datasets demonstrate that the proposed model can detect the escape events more effectively from dense crowd.