• Title/Summary/Keyword: probability models

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Stochastic modelling fatigue crack evolution and optimum maintenance strategy for composite blades of wind turbines

  • Chen, Hua-Peng;Zhang, Chi;Huang, Tian-Li
    • Structural Engineering and Mechanics
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    • v.63 no.6
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    • pp.703-712
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    • 2017
  • The composite blades of offshore wind turbines accumulate structural damage such as fatigue cracking due to harsh operation environments during their service time, leading to premature structural failures. This paper investigates various fatigue crack models for reproducing crack development in composite blades and proposes a stochastic approach to predict fatigue crack evolution and to analyse failure probability for the composite blades. Three typical fatigue models for the propagation of fatigue cracks, i.e., Miner model, Paris model and Reifsnider model, are discussed to reproduce the fatigue crack evolution in composite blades subjected to cyclical loadings. The lifetime probability of fatigue failure of the composite blades is estimated by stochastic deterioration modelling such as gamma process. Based on time-dependent reliability analysis and lifecycle cost analysis, an optimised maintenance policy is determined to make the optimal decision for the composite blades during the service time. A numerical example is employed to investigate the effectiveness of predicting fatigue crack growth, estimating the probability of fatigue failure and evaluating an optimal maintenance policy. The results from the numerical study show that the stochastic gamma process together with the proper fatigue models can provide a useful tool for remaining useful life predictions and optimum maintenance strategies of the composite blades of offshore wind turbines.

Empirical Analysis on the Relationship between R&D Inputs and Performance Using Successive Binary Logistic Regression Models (연속적 이항 로지스틱 회귀모형을 이용한 R&D 투입 및 성과 관계에 대한 실증분석)

  • Park, Sungmin
    • Journal of Korean Institute of Industrial Engineers
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    • v.40 no.3
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    • pp.342-357
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    • 2014
  • The present study analyzes the relationship between research and development (R&D) inputs and performance of a national technology innovation R&D program using successive binary Logistic regression models based on a typical R&D logic model. In particular, this study focuses on to answer the following three main questions; (1) "To what extent, do the R&D inputs have an effect on the performance creation?"; (2) "Is an obvious relationship verified between the immediate predecessor and its successor performance?"; and (3) "Is there a difference in the performance creation between R&D government subsidy recipient types and between R&D collaboration types?" Methodologically, binary Logistic regression models are established successively considering the "Success-Failure" binary data characteristic regarding the performance creation. An empirical analysis is presented analyzing the sample n = 2,178 R&D projects completed. This study's major findings are as follows. First, the R&D inputs have a statistically significant relationship only with the short-term, technical output, "Patent Registration." Second, strong dependencies are identified between the immediate predecessor and its successor performance. Third, the success probability of the performance creation is statistically significantly different between the R&D types aforementioned. Specifically, compared with "Large Company", "Small and Medium-Sized Enterprise (SMS)" shows a greater success probability of "Sales" and "New Employment." Meanwhile, "R&D Collaboration" achieves a larger success probability of "Patent Registration" and "Sales."

Breakdown Characteristics and Survival Probability of Turn-to- Turn Models for a HTS Transformer

  • Cheon H.G.;Baek S.M.;Seong K.C.;Kim H.J.;Kim S.H.
    • Progress in Superconductivity and Cryogenics
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    • v.7 no.2
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    • pp.21-26
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    • 2005
  • Breakdown characteristics and survival probability of turn-to-turn models were investigated under ac and impulse voltage at 77K. For experiments, two test electrode models were fabricated: One is point contact model and the other is surface contact model. Both are made of copper wrapped by O.025mm thick polyimide film(Kapton). The experimental results were analyzed statistically using Weibull distribution in order to examine the wrapping number effects on voltage-time characteristics under ac voltage as well as under impulse voltage in LN$_{2}$. Also survival analysis were performed according to the Kaplan-Meier method. The breakdown voltages of surface contact model are lower than that of point contact model, because the contact area of surface contact model is wider than that of point contact model. Besides, the shape parameter of point contact model is a little bit larger than that of surface contact model. The time to breakdown t$_{50}$ is decreased as the applied voltage is increased, and the lifetime indices slightly are increased as the number of layers is increased. According to the increasing applied voltage and decreasing wrapping number, the survival probability is increased.

Development of Empirical Space Weather Models based on Solar Information

  • Moon, Yong-Jae;Kim, Rok-Soon;Park, Jin-Hye;Jin, Kang
    • The Bulletin of The Korean Astronomical Society
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    • v.36 no.2
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    • pp.90.1-90.1
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    • 2011
  • We are developing empirical space weather (geomagnetic storms, solar proton events, and solar flares) forecast models based on solar information. These models have been set up with the concept of probabilistic forecast using historical events. Major findings can be summarized as follows. First, we present a concept of storm probability map depending on CME parameters (speed and location). Second, we suggested a new geoeffective CME parameter, earthward direction parameter, directly observable from coronagraph observations, and demonstrated its importance in terms of the forecast of geomagnetic storms. Third, the importance of solar magnetic field orientation for storm occurrence was examined. Fourth, the relationship among coronal hole-CIR-storm relationship has been investigated, Fifth, the CIR forecast based on coronal hole information is possible but the storm forecast is challenging. Sixth, a new solar proton event (flux, strength, and rise time) forecast method depending on flare parameters (flare strength, duration, and longitude) as well as CME parameter (speed, angular width, and longitude) has been suggested. Seventh, we are examining the rates and probability of solar flares depending on sunspot McIntosh classification and its area change (as a proxy of flux change). Our results show that flux emergence greatly enhances the flare probability, about two times for flare productive sunspot regions.

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Channel Access Control Method for the CDMA Packet Service System (CDMA 패킷 서비스 시스템에서 채널 엑세스 제어 기법 연구)

  • 이강원
    • Journal of the Korean Operations Research and Management Science Society
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    • v.28 no.3
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    • pp.169-184
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    • 2003
  • In the IS-95 packet service system, the radio channels are generally classified into the dedicated and the common traffic channels. In this paper, a common traffic channel access method is proposed for the COMA packet service system to enhance the radio resource utilization while guaranteeing QoS to the users. The proposed method is based on the permission probability for the common traffic channel user. To derive permission probability, optimization models are developed for two different QoS constraints. Approximation methods are also developed.

Development of Gap Acceptance Models for Permitted Left Turn Intersections (비보호좌회전에서의 간격수락 행태모형 개발)

  • Lee, Chung Won;Lee, Dong Min;Hwang, Soon Cheon
    • International Journal of Highway Engineering
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    • v.18 no.5
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    • pp.95-103
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    • 2016
  • PURPOSES : Permitted left turn is a turning maneuver in which a vehicle turns left using a gap between oncoming vehicles, called gap acceptance, and it enables for more efficient traffic operation at intersections. In Korea, the permitted left turn has not been a common maneuver at signalized or un-signalized intersections. However, many experts and the Police Agency tried to apply this effective turning maneuver at intersections in Korea since 2010. Though the investigation of gap acceptance is significantly important in understanding a driver's behavior at intersections, there have not been many studies about this topic, specifically a study to develop probability models of gap acceptance behavior. METHODS : In this study, the probability model of gap acceptance behavior for a permitted left turn was developed based on observational field studies. To develop the model, seven variables were analyzed including gap, waiting time, traffic volume, conflict-flow vehicle type, left-turning vehicle type, the number of lane, and time. RESULTS : In the final model, gap and left-turning vehicle type were found to be significant influencing factors. CONCLUSIONS : Through this model development, it was concluded that as the gap size increased, the probability of gap acceptance was higher. Moreover, when a left-turning vehicle was a passenger car, the probability of gap acceptance was higher than compared to large size buses or freight cars.

Slope Stability Analysis Considering Multi Failure Mode (다중파괴모드를 고려한 사면안정해석)

  • Kim, Hyun-Ki;Kim, Soo-Sam
    • Journal of the Korean Society for Railway
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    • v.14 no.1
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    • pp.24-30
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    • 2011
  • Conventional slope stability analysis is focused on calculating minimum factor of safety or maximum probability of failure. To minimize inherent uncertainty of soil properties and analytical model and to reflect various analytical models and its failure shape in slope stability analysis, slope stability analysis method considering simultaneous failure probability for multi failure mode was proposed. Linear programming recently introduced in system reliability analysis was used for calculation of simultaneous failure probability. System reliability analysis for various analytical models could be executed by this method. For application analysis for embankment, the results of this method shows that system stability of embankment calculate quantitatively.

A joint probability distribution model of directional extreme wind speeds based on the t-Copula function

  • Quan, Yong;Wang, Jingcheng;Gu, Ming
    • Wind and Structures
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    • v.25 no.3
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    • pp.261-282
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    • 2017
  • The probabilistic information of directional extreme wind speeds is important for precisely estimating the design wind loads on structures. A new joint probability distribution model of directional extreme wind speeds is established based on observed wind-speed data using multivariate extreme value theory with the t-Copula function in the present study. At first, the theoretical deficiencies of the Gaussian-Copula and Gumbel-Copula models proposed by previous researchers for the joint probability distribution of directional extreme wind speeds are analysed. Then, the t-Copula model is adopted to solve this deficiency. Next, these three types of Copula models are discussed and evaluated with Spearman's rho, the parametric bootstrap test and the selection criteria based on the empirical Copula. Finally, the extreme wind speeds for a given return period are predicted by the t-Copula model with observed wind-speed records from several areas and the influence of dependence among directional extreme wind speeds on the predicted results is discussed.

Performance Models of Multi-stage Bernoulli Lines with Multiple Product and Dedicated Buffers (다품종 제품과 전용 대기공간을 고려한 다단계 베르누이 라인을 위한 성능 모델)

  • Park, Kyungsu;Han, Jun-Hee;Kim, Woo-Sung
    • Journal of Korean Society of Industrial and Systems Engineering
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    • v.44 no.3
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    • pp.22-32
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    • 2021
  • To meet rapidly changing market demands, manufacturers strive to increase both of productivity and diversity at the same time. As a part of those effort, they are applying flexible manufacturing systems that produce multiple types and/or options of products at a single production line. This paper studies such flexible manufacturing system with multiple types of products, multiple Bernoulli reliability machines and dedicated buffers between them for each of product types. As one of the prevalent control policies, priority based policy is applied at each machines to select the product to be processed. To analyze such system and its performance measures exactly, Markov chain models are applied. Because it is too complex to define all relative transient and its probabilities for each state, an algorithm to update transient state probability are introduced. Based on the steady state probability, some performance measures such as production rate, WIP-based measures, blocking probability and starvation probability are derived. Some system properties are also addressed. There is a property of non-conservation of flow, which means the product ratio at the input flow is not conserved at the succeeding flows. In addition, it is also found that increased buffer capacity does not guarantee improved production rate in this system.