• Title/Summary/Keyword: Sampled-data

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On using computational versus data-driven methods for uncertainty propagation of isotopic uncertainties

  • Radaideh, Majdi I.;Price, Dean;Kozlowski, Tomasz
    • Nuclear Engineering and Technology
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    • v.52 no.6
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    • pp.1148-1155
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    • 2020
  • This work presents two different methods for quantifying and propagating the uncertainty associated with fuel composition at end of life for cask criticality calculations. The first approach, the computational approach uses parametric uncertainty including those associated with nuclear data, fuel geometry, material composition, and plant operation to perform forward depletion on Monte-Carlo sampled inputs. These uncertainties are based on experimental and prior experience in criticality safety. The second approach, the data-driven approach relies on using radiochemcial assay data to derive code bias information. The code bias data is used to perturb the isotopic inventory in the data-driven approach. For both approaches, the uncertainty in keff for the cask is propagated by performing forward criticality calculations on sampled inputs using the distributions obtained from each approach. It is found that the data driven approach yielded a higher uncertainty than the computational approach by about 500 pcm. An exploration is also done to see if considering correlation between isotopes at end of life affects keff uncertainty, and the results demonstrate an effect of about 100 pcm.

Functional clustering for clubfoot data: A case study (클럽발 자료를 위한 함수적 군집 분석: 사례연구)

  • Lee, Miae;Lim, Johan;Park, Chungun;Lee, Kyeong Eun
    • Journal of the Korean Data and Information Science Society
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    • v.25 no.5
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    • pp.1069-1077
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    • 2014
  • A clubfoot is a kind of congenital deformity of foot, which is internally rotated at the ankle. In this paper, we are going to cluster the curves of relative differences between regular and operated feet. Since these curves are irregular and sparsely sampled, general clustering models could not be applied. So the clustering model for sparsely sampled functional data by James and Sugar (2003) are applied and parameters are estimated using EM algorithm. The number of clusters is determined by the distortion function (Sugar and James, 2003) and two clusters of the curves are found.

Sampled-data Fuzzy Control for Nonlinear Neutral Systems (샘플치 퍼지 제어기 설계를 이용한 비선형 뉴트럴 시스템 제어기 설계)

  • Song, Min-Kook;Joo, Young-Hoon;Park, Jin-Bae
    • Proceedings of the KIEE Conference
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    • 2008.04a
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    • pp.195-196
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    • 2008
  • This paper presents the stability analysis and design for a sampled-data fuzzy control system with neutral type of time delay. The sampling activity and neutral type of time delay will complicate the nonlinear system dynamics. And it make the stability analysis much more difficult than that for a continuous-time fuzzy control system. Based on the fuzzy control approach, linear matrix inequality (LMI)-based stability conditions are derived to guarantee the neutral T-S fuzzy system stability. Finally, an example is provided to illustrate the effectiveness of the proposed approach.

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Likelihood Based Confidence Intervals for the Difference of Proportions in Two Doubly Sampled Data with a Common False-Positive Error Rate

  • Lee, Seung-Chun
    • Communications for Statistical Applications and Methods
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    • v.17 no.5
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    • pp.679-688
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    • 2010
  • Lee (2010) developed a confidence interval for the difference of binomial proportions in two doubly sampled data subject to false-positive errors. The confidence interval seems to be adequate for a general double sampling model subject to false-positive misclassification. However, in many applications, the false-positive error rates could be the same. On this note, the construction of asymptotic confidence interval is considered when the false-positive error rates are common. The coverage behaviors of nine likelihood based confidence intervals are examined. It is shown that the confidence interval based Rao score with the expected information has good performance in terms of coverage probability and expected width.

A Study on Fault Location Using Wavelet in 154kV Transmission Power Cable (154kV 지중송전케이블에서 Wavelet을 이용한 Fault Location에 관한 연구)

  • Lee, Jun-Sung;Lee, Jong-Beom;Moon, Sung-Chall
    • Proceedings of the KIEE Conference
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    • 2000.07a
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    • pp.437-439
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    • 2000
  • This paper describes a fault location technique using wavelets in underground transmission cable system Estimation of fault location is performed using data sampled at two ends of underground system. In the case of 50% fault of total underground transmission line, fault location is calculated using sampled single-end data in underground transmission line. Traveling wave is utilized in capturing the travel time of the transients along the monitored lines between the relay and the fault point. This travel time information is provided by the wavelet. Simulation was performed using EMTP. ATP Draw and MATLAB. The results of fault location shown in this paper will be evaluated as an effective suggestion for fault to location in real underground transmission line.

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Design of Optimal Sampled-Data Controller for Continuous-Time Chatoic Systems

  • Park, Kwang-Sung;Park, Jin-Bae;Park, Yoon-Ho
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.38.5-38
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    • 2001
  • In this paper, we propose new digital optimal control approach for controlling continuous-time nonlinear chaotic systems, which show very complex behavior and cannot be easily controlled by conventional control methods. Most real systems are represented as continuous-time system, whereas some control methods should be implemented under the condition of computer-based platforms, which are discrete-time systems. To achieve the control objective for chaotic systems successfully, the sampled-data controller, which considers the inter-sample behavior of the continuous-time systems effectively, should be needed. The proposed optimal controller is designed based on the linearized estimation model of chaotic systems. By the computer simulation, we show the control ...

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Pattern Recognition of Rotor Fault Signal Using Bidden Markov Model (은닉 마르코프 모형을 이용한 회전체 결함신호의 패턴 인식)

  • Lee, Jong-Min;Kim, Seung-Jong;Hwang, Yo-Ha;Song, Chang-Seop
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.27 no.11
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    • pp.1864-1872
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    • 2003
  • Hidden Markov Model(HMM) has been widely used in speech recognition, however, its use in machine condition monitoring has been very limited despite its good potential. In this paper, HMM is used to recognize rotor fault pattern. First, we set up rotor kit under unbalance and oil whirl conditions. Time signals of two failure conditions were sampled and translated to auto power spectrums. Using filter bank, feature vectors were calculated from these auto power spectrums. Next, continuous HMM and discrete HMM were trained with scaled forward/backward variables and diagonal covariance matrix. Finally, each HMM was applied to all sampled data to prove fault recognition ability. It was found that HMM has good recognition ability despite of small number of training data set in rotor fault pattern recognition.

A Design of the Multirate Digital Controller using Sampled Data $H_2$ Optimization (샘플치 $H_2$ 최적화를 이용한 멀티레이트 디지털 제어기 설계)

  • 박종우;이상철;곽칠성
    • Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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    • 2001.10a
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    • pp.271-274
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    • 2001
  • In this paper, optimal digital design is studied within the framework of sampled-data control theory. In particular, multirate discretization of analog controller is considered using an H$_2$optimality criterion. Solutions are obtained via multirate H$_2$optimization with a causality constraint due to the multirate structure. In design example, the comparison of the proposed methods is made with the conventional discretization methods, and demonstrate the superiority of the multirate design method.

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