• Title/Summary/Keyword: Weibull Reliability Analysis

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Joint distribution of wind speed and direction in the context of field measurement

  • Wang, Hao;Tao, Tianyou;Wu, Teng;Mao, Jianxiao;Li, Aiqun
    • Wind and Structures
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    • v.20 no.5
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    • pp.701-718
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    • 2015
  • The joint distribution of wind speed and wind direction at a bridge site is vital to the estimation of the basic wind speed, and hence to the wind-induced vibration analysis of long-span bridges. Instead of the conventional way relying on the weather stations, this study proposed an alternate approach to obtain the original records of wind speed and the corresponding directions based on field measurement supported by the Structural Health Monitoring System (SHMS). Specifically, SHMS of Sutong Cable-stayed Bridge (SCB) is utilized to study the basic wind speed with directional information. Four anemometers are installed in the SHMS of SCB: upstream and downstream of the main deck center, top of the north and south tower respectively. Using the recorded wind data from SHMS, the joint distribution of wind speed and direction is investigated based on statistical methods, and then the basic wind speeds in 10-year and 100-year recurrence intervals at these four key positions are calculated. Analytical results verify the reliability of the recorded wind data from SHMS, and indicate that the joint probability model for the extreme wind speed at SCB site fits well with the Weibull model. It is shown that the calculated basic wind speed is reduced by considering the influence of wind direction. Compared to the design basic wind speed in the Specification of China, basic wind speed considering the influence of direction or not is much smaller, indicating a high safety coefficient in the design of SCB. The results obtained in this study can provide not only references for further wind-resistance research of SCB, but also improve the understanding of the safety coefficient for wind-resistance design of other engineering structures in the similar area.

The Comparative Study for Property of Learning Effect based on Software Reliability Model using Doubly Bounded Power Law Distribution (이중 결합 파우어 분포 특성을 이용한 유한고장 NHPP모형에 근거한 소프트웨어 학습효과 비교 연구)

  • Kim, Hee Cheul;Kim, Kyung-Soo
    • Convergence Security Journal
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    • v.13 no.1
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    • pp.71-78
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    • 2013
  • In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The doubly bounded power law distribution model makeup Weibull distribution applied to distribution was based on finite failure NHPP. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R^2$.

The Study of NHPP Software Reliability Model from the Perspective of Learning Effects (학습 효과 기법을 이용한 NHPP 소프트웨어 신뢰도 모형에 관한 연구)

  • Kim, Hee-Cheul;Shin, Hyun-Cheul
    • Convergence Security Journal
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    • v.11 no.1
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    • pp.25-32
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    • 2011
  • In this study, software products developed in the course of testing, software managers in the process of testing software test and test tools for effective learning effects perspective has been studied using the NHPP software. The Weibull distribution applied to distribution was based on finite failure NHPP. Software error detection techniques known in advance, but influencing factors for considering the errors found automatically and learning factors, by prior experience, to find precisely the error factor setting up the testing manager are presented comparing the problem. As a result, the learning factor is greater than automatic error that is generally efficient model could be confirmed. This paper, a numerical example of applying using time between failures and parameter estimation using maximum likelihood estimation method, after the efficiency of the data through trend analysis model selection were efficient using the mean square error and $R_{sq}$.

Microstructure, Tensile Strength and Probabilistic Fatigue Life Evaluation of Gray Cast Iron (회주철의 미세구조와 인장거동 분석 및 확률론적 피로수명평가)

  • Sung, Yong Hyeon;Han, Seung-Wook;Choi, Nak-Sam
    • Transactions of the Korean Society of Mechanical Engineers A
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    • v.41 no.8
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    • pp.721-728
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    • 2017
  • High-grade gray cast iron (HCI350) was prepared by adding Cr, Mo and Cu to the gray cast iron (GC300). Their microstructure, mechanical properties and fatigue strength were studied. Cast iron was made from round bar and plate-type castings, and was cut and polished to measure the percentage of each microstructure. The size of flake graphite decreased due to additives, while the structure of high density pearlite increased in volume percentage improving the tensile strength and fatigue strength. Based on the fatigue life data obtained from the fatigue test results, the probability - stress - life (P-S-N) curve was calculated using the 2-parameter Weibull distribution to which the maximum likelihood method was applied. The P-S-N curve showed that the fatigue strength of HCI350 was significantly improved and the dispersion of life data was lower than that of GC300. However, the fatigue life according to fatigue stress alleviation increased further. Data for reliability life design was presented by quantitatively showing the allowable stress value for the required life cycle number using the calculated P-S-N curve.