• Journal of Korean Institute of Industrial Engineers
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• v.33 no.1
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• pp.70-75
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• 2007

This paper discusses condition based preventive replacement for deteriorating systems. The system continuouslydeteriorates in time and fails at any deterioration level which is always monitored, It is replaced at failure or atsome deteriorated level preventively before failure. The deterioration process is represented by a Weibulldistribution with a time-linear scale parameter. The cost rate function is formed considering replacement costand opportunity loss cost and deterioration dependent failure distribution, If the system has an increasingdeterioration dependent failure rate, the optimal deterioration level for preventive replacement can be determinedfrom minimizing the cost rate. An illustrative example is given for a Weibull deterioration dependent failuredistribution.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.13 no.4
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• pp.141-150
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• 1993

For the three parameter Weibull distribution, the parameter estimation techniques are applied and the asymptotic variances of the quantile to obtain the confidence limits for a given return period are derived. Three estimation techniques are used for these purposes: the methods of moments, maximum likelihood and probability weighted moments. The three parameter Weibull distribution as a flood frequency model is applied to actual flood data.

• Proceedings of the IEEK Conference
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• 2003.07e
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• pp.2184-2187
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• 2003

Quantizers for digital coding systems are usually optimized with respect to a model of the probability density function of the random variable to be quantized. Thus a mismatch of the quantizer relative to the actual statistics of the random variable may be unavoidable. This paper presents the results of an experimental investigation of mismatched quantizers. For the modeling of the source statistics, various types of the Weibull distribution are used, and the optimization of the quantizer is carried with respect to the minimum mean-square error (mse) criterion. The goal of this paper is to find an estimate formula for the mismatched quantizer on Weibull sources.

• Wind and Structures
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• v.28 no.1
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• pp.63-70
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• 2019

Due to developing environmental concern use of renewable energy source is very essential. The great demand for the energy supply coupled with inadequate energy sources creates an emergency to find a new solution for the energy shortage. The appropriate wind energy distribution is the fundamental requirement for the assessment of wind energy potential available at the particular site essential for the design of wind farms. Hence the proper specification of the wind speed distribution plays a vital role. In this paper the Bimodal Weibull distribution is used to estimate the Capacity factor at the proposed site. The shape and scale parameters estimated using Maximum likelihood method is used as the initial value for extrapolation. Application of this model will give an accurate result overwhelming the concept of overestimation or underestimation of Capacity factor.

• Journal of the Korean Data and Information Science Society
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• v.16 no.4
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• pp.1017-1026
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• 2005

We consider the problem of modeling count data where the observation period is determined by the survival time of the individual under study. We assume random effects or frailty model to allow for a possible association between the death times and the counts. We assume that, given a random effect, the death times follow a Weibull distribution with a rate that depends on some covariates. For the counts, given the random effect, a Poisson process is assumed with the intensity depending on time and the covariates. A gamma model is assumed for the random effect. Maximum likelihood estimators of the model parameters are obtained. The model is applied to data set of patients with breast cancer who received a bone marrow transplant. A model for the time to death and the number of supportive transfusions a patient received is constructed and consequences of the model are examined.

• Journal of Mechanical Science and Technology
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• v.19 no.6
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• pp.1280-1289
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• 2005

This paper presents the effects of corrosion environments of failure pressure model for buried pipelines on failure prediction by using a failure probability. The FORM (first order reliability method) is used in order to estimate the failure probability in the buried pipelines with corrosion defects. The effects of varying distribution types of random variables such as normal, lognormal and Weibull distributions on the failure probability of buried pipelines are systematically investigated. It is found that the failure probability for the MB31G model is larger than that for the B31G model. And the failure probability is estimated as the largest for the Weibull distribution and the smallest for the normal distribution. The effect of data scattering in corrosion environments on failure probability is also investigated and it is recognized that the scattering of wall thickness and yield strength of pipeline affects the failure probability significantly. The normalized margin is defined and estimated. Furthermore, the normalized margin is used to predict the failure probability using the fitting lines between failure probability and normalized margin.

• Computational Structural Engineering
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• v.1 no.1
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• pp.113-122
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• 1988

A practical model for predicting the risk of fatigue failure of steel highway bridges is developed in this study. The proposed model is derived from fatigue reliability methods by incorporating various factors which may affect the fatigue life of bridges. The fatigue reliability function is assumed to follow the Weibull distribution. The computational form of the Weibull is adopted from Ang-Munse's approach that includes all the statistical uncertainties of the fatigue life of steel members and the stress ranges under variable amplitude loadings. The model accounts for the variation in ADTT, the change in stress history and the effects of inspections, which may occur during the serivce life of bridges. Stress range histograms are collected from the random stress spectra based on the field measurements of an existing bridge, and, thus, the resulting stress range frequency distribution is modelled with a beta distribution. The results of applications of the proposed fatigue analysis methods to an existing bridge show that the proposed models with the computer program developed for numerical computations can be used as a practical tool for the fatigue rating or for the predictions of the remaining fatigue life of deteriorated existing steel bridges.

• Journal of the Korea Concrete Institute
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• v.16 no.5 s.83
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• pp.581-589
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• 2004

This paper compares the fatigue behaviors of concretes subjected to flexural and split-tensional loadings, and proposes the fatigue reliability models based on experimental results and reliability analysis. The fatigue tests were performed for the specimens of $150 mm{\times}75 mm$ split tensional cylinders and $150 mm{\times}150 mm{\times}550 mm$ flexural beams under constant loadings at three levels (70, 80 and $90\%$) with 0.1 stress ratio, 20 Hz loading speed and sine wave. The reliability analysis on fatigue data was based on Weibull distribution of two-parameters. From fatigue test results, two criteria were proposed to reject the experimental fatigue data because of statistical variation of concrete fatigue data. Two parameters ($\alpha$and u) of Weibull distribution were obtained using graphical method, moment method and maximum likelihood method. The probability density function(P.D.F) and cumulative distribution function(C.D.F) of the Weibull distribution for fatigue life of pavement concrete were derived for various stress levels using parameters, $\alpha$ and u. The goodness-of-fit test by Kolmogorov-Smirnov test was acceptable at $5\%$ level of significance. Based on reliability analysis, a fatigue model for pavement concrete was proposed and compared from existing models.

• Journal of Biomedical Engineering Research
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• v.37 no.1
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• pp.21-30
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• 2016

Weibull distribution with two parameters, shape (k) and scale (s) parameters are used to model the fatigue failure analysis due to periodic vortex shedding of the synovial fluid in knee joints. In order to determine the later parameter, a suitable statistical model is required for velocity distribution of synovial fluid flow. Hence, wide applicability of Weibull distribution in life testing and reliability analysis can be applied to describe the probability distribution of synovial fluid flow velocity. In this work, comparisons of three most widely used methods for estimating Weibull parameters are carried out; i.e. the least square estimation method (LSEM), maximum likelihood estimator (MLE) and the method of moment (MOM), to study fatigue failure of bone joint due to periodic vortex shedding of synovial fluid. The performances of these methods are compared through the analysis of computer generated synovial fluidflow velocity distribution in the physiological range. Significant values for the (k) and (s) parameters are obtained by comparing these methods. The criterions such as root mean square error (RMSE), coefficient of determination ($R^2$), maximum error between the cumulative distribution functions (CDFs) or Kolmogorov-Smirnov (K-S) and the chi square tests are used for the comparison of the suitability of these methods. The results show that maximum likelihood method performs well for most of the cases studied and hence recommended.

• Water Engineering Research
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• v.1 no.1
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• pp.11-23
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• 2000

Regional flood frequency analysis has been developed by employing the nearby site's information to improve a precision in estimating flood quantiles at the site of interest. In this paper, single site and regional flood frequency analyses were compared based of the 2-parameter Weibull model. For regional analysis, two approaches were employed. The First one is to use the asymptotic variances of the quantile estimators derived based of the assumption that all sites including the site of interest are independent each other. This approach may give the maximum regional gain due to the spatial independence assumption among sites. The second one in Hosking's regional L-moment algorithm. These methods were applied to annual flood data. As the results, both methods generally showed the regional gain at the site of interest depending on grouping the sites as homogeneous. And asymptotic formula generally shows smaller variance than those from Hosking's algorithm. If the shape parameter of the site of interest from single site analysis is quite different from that from regional analysis then Hosking's results might be better than the asymptotic ones because the formula was derived based on the assumption that all sites have the same regional shape parameter. Furthermore, in such a case, regional analysis might be worse than single site analysis in the sense of precision of flood quantile estimation. Even though the selected sites may satisfy Hosking's criteria, regional analysis may not give a regional gain for specific and nonexceedance probabilities.