• Title/Summary/Keyword: Random Factor Method

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On desirable conditions for a random number used in the random sampling method

  • Harada, Hiroshi;Kashiwagi, Hiroshi;Takada, Tadashi
    • 제어로봇시스템학회:학술대회논문집
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    • 1990.10b
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    • pp.1295-1299
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    • 1990
  • A new method called random sampling method has been proposed for generation of binary random sequences. In this paper, a new concept, called merit factor Fn, is proposed for evaluating the randomness of the binary random sequences generated by the random sampling method. Using this merit factor Fn, some desirable conditions are investigated for uniform random numbers used in the random sampling method.

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Homogenized thermal properties of 3D composites with full uncertainty in the microstructure

  • Ma, Juan;Wriggers, Peter;Li, Liangjie
    • Structural Engineering and Mechanics
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    • v.57 no.2
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    • pp.369-387
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    • 2016
  • In this work, random homogenization analysis for the effective thermal properties of a three-dimensional composite material with unidirectional fibers is presented by combining the equivalent inclusion method with Random Factor Method (RFM). The randomness of the micro-structural morphology and constituent material properties as well as the correlation among these random parameters are completely accounted for, and stochastic effective thermal properties as thermal expansion coefficients as well as their correlation are then sought. Results from the RFM and the Monte-Carlo Method (MCM) are compared. The impact of randomness and correlation of the micro-structural parameters on the random homogenized results is revealed by two methods simultaneously, and some important conclusions are obtained.

Evaluation of randomness of binary random sequence

  • Harada, Hiroshi;Kashiwagi, Hiroshi;Takada, Tadashi
    • 제어로봇시스템학회:학술대회논문집
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    • 1989.10a
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    • pp.979-983
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    • 1989
  • This paper proposes a new concept, called merit factor Fr, for evaluating the randomness of binary random sequences. The merit factor Fr is obtained from the expected values of the autocorrelation function of the binary random sequence. Using this merit factor Fr, randomness of the binary random sequences generated by the random sampling method is evaluated.

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Harmonic Intensity Reduction Technique for Single Phase Switched Reluctance Motor Drives Using a New Random PWM Scheme

  • Nguyen, Minh-Khai;Jung, Young-Gook;Yang, Hyong-Yeol;Lim, Young-Cheol
    • Journal of Power Electronics
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    • v.10 no.1
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    • pp.51-57
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    • 2010
  • This paper proposes a new random switching strategy using a DSP TMS320F2812 to reduce the harmonics spectra of single phase switched reluctance motors. The proposed method combines the random turn-on/off angle technique and the random pulse width modulation technique. A harmonic spread factor (HSF) is used to evaluate the random modulation scheme. In order to confirm the effectiveness of the proposed method an experiment was conducted. The experimental results show that the harmonic intensity of the output voltage for the proposed method is better than that for conventional methods.

Outlier Detection in Random Effects Model Using Fractional Bayes Factor

  • Chung, Younshik
    • Communications for Statistical Applications and Methods
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    • v.7 no.1
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    • pp.141-150
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    • 2000
  • In this paper we propose a method of computing Bayes factor to detect an outlier in a random effects model. When no information is available and hence improper noninformative priors should be used Bayes factor includes the unspecified constants and has complicated computational burden. To solve this problem we use the fractional Bayes factor (FBF) of O-Hagan(1995) and the generalized Savage0-Dickey density ratio of Verdinelli and Wasserman (1995) The proposed method is applied to outlier deterction problem We perform a simulation of the proposed approach with a simulated data set including an outlier and also analyze a real data set.

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Stability analysis of closely-spaced tunnel using RFEM (확률유한요소 해석에 의한 근접터널 안정성 분석)

  • Kim, Sang-Gyun
    • Journal of Korean Tunnelling and Underground Space Association
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    • v.10 no.4
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    • pp.349-360
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    • 2008
  • In this paper, the modeling procedure of random field with an elasto-plastic finite element algorithm and probability of failure on closely-spaced tunnel were investigated. Local average subdivision (LAS) method which can generate discrete random variables fast and accurately as well as change the resolution in certain region was used. And correlated value allocating and weighted average method were suggested to implement geometrical characteristics of tunnel. After the probability of failure on the test problem was thoroughly investigated using random finite element method, the results were compared with the deterministic strength reduction factor method and single random variable method. Of particular importance in this work, is the conclusion that the probability of failure determined by simplified probabilistic analysis, in which spatial variability is ignored by assuming perfect correlation, can be estimated from the safety factor determined by strength reduction factor method. Also, single random variable method can lead to unconservative estimates of the probability of failure.

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A Quantitative Evaluation of ${\Delta}K_{eff}$ Estimation Methods Based on Random Loading Crack Growth Data. (랜덤하중하의 피로균열진전 데이터를 이용한 ${\Delta}K_{eff}$ 평가법의 정량적 평가)

  • Koo, Ja-Suk;Song, Ji-Ho;Kang, Jae-Youn
    • Proceedings of the KSME Conference
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    • 2004.11a
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    • pp.208-213
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    • 2004
  • Methods for estimation of the effective stress intensity factor range (${\Delta}K_{eff}$) are evaluated for narrow and wide band random loading crack growth test data of 2024-T351 aluminum alloy. Three methods of determining $K_{op}$, visual measurement, ASTM offset compliance method, and the neural network method proposed by Kang and Song, and three methods of estimating ${\Delta}K_{eff}$, conventional, the 2/PI0 and 2/PI methods proposed by Donald and Paris, are compared in a quantitative manner by using the results of fatigue crack growth life prediction under random loading. For all $K_{op}$ determination methods discussed, the 2/PI0 and 2/PI methods of estimating ${\Delta}K_{eff}$ provide better results than conventional method for narrow and wide band random loading data.

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An Improvement for Determining Response Modification Factor in Bridge Load Rating (응력보정계수 산정 방법 개선)

  • Koo, Bong-Kuen;Shin, Jae-In;Lee, Sang-Soon
    • Journal of the Korea institute for structural maintenance and inspection
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    • v.5 no.1
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    • pp.169-175
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    • 2001
  • Bridge load rating calculations provide a basis for determining the safe load capacity of bridge. Load rating requires engineering judgement in determining a rating value that is applicable to maintaining the safe use of the bridge and arriving at posting and permit decisions. Load testing is an effective means in calculating the rating value of bridge. In Korea, load carrying capacity of bridge is modified by response modification factor that is determined from comparisons of measured values and analysis results. The response modification factor may be corrupted by vehicle location error that is defined as the gap of test vehicle location between load testing and analysis. In this study, the effects of vehicle location error to structural response and response modification factor are investigated, and a new method for evaluating response modification factor is proposed. The random data analysis shows that the proposed method is less sensitive to vehicle location error than the present method.

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Variance components in one-factor random model by projections (사영을 이용한 일원 분산성분)

  • Choi, Jae-Sung
    • Journal of the Korean Data and Information Science Society
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    • v.22 no.3
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    • pp.381-387
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    • 2011
  • This paper suggests a method for estimating components of variance in one-factor random model. Estimates of variance components are given by the method of moments. Sums of squares due to variance sources are obtained by projections. This paper also shows how to use eigenvalues for getting the coefficients of variance components in the expression of the expectations of the mean squares. The suggested method shows easier and faster than the method of Harley's synthesis.

Derivation of Expected Mean Squares (EMS) Using Venn Diagram by the Type of Experimental Design (실험설계 유형별 Venn Diagram을 이용한 EMS 도출)

  • Choi, Sung-Woon
    • Proceedings of the Safety Management and Science Conference
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    • 2011.04a
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    • pp.695-699
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    • 2011
  • The study presents an efficient design method of Venn Diagram that can be used when implementing the quality design of experiments based on generalizability theory. The paper examines four mixed and combined models that are designed by fixed factor, random factor, crossed factor and nested factor. The models considered in this research are $A^*{\times}B^*{\times}C$, (B: $A^*$)${\times}C$, $A{\times}B{\times}C$ and (B: A)${\times}C$.

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