• Wind and Structures
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• v.28 no.6
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• pp.369-380
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• 2019

Statistical distributions are very useful in describing wind speed characteristics and in predicting wind power potential of a specified region. Although the Weibull distribution is the most popular one in wind energy literature, it does not seem to be able to perfectly fit all the investigated wind speed data in nature. Thus, many studies are still being conducted to find flexible distribution for modelling wind speed data. In this study, we propose a new Odd-Burr Rayleigh distribution for wind speed characterization. The Odd-Burr Rayleigh distribution with two shape parameters is flexible enough to model different shapes of wind speed data and thus it can be an alternative wind speed distribution for the assessment of wind energy potential. Therefore, suitability of the Odd-Burr Rayleigh distribution is investigated on real wind speed data taken from different regions in the South Africa. Numerical results of the conducted analysis confirm that the new Odd-Burr Rayleigh distribution is suitable for modelling most of the considered real wind speed cases and it also can be used for predicting wind power.

• Journal of Korean Society for Quality Management
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• v.29 no.3
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• pp.49-65
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• 2001

This paper presents new compromise ALT plan which is applied to situations that true relationship between stress and parameters is not known exactly. The assumed failure distribution of this study is one of location-scale family, i. e., exponential, Weibull, and lognormal distributions which have been ones of the popular choices of failure distributions. The method of applying the stress is constant, and the censoring mechanism is Type I censoring. Compared with existing compromise plans under true simple linear model in terms of statistical efficiency, the efficiency of new compromise plan is better than the corresponding other compromise ones in most cases. For case when true model is quadratic, this plan can be used without any severe loss in statistical efficiency. The proposed new compromise ALT plan is illustrated with a numerical example and sensitivity analyses are conducted to study effects of pre-estimates of design parameters.

• Communications of the Korean Mathematical Society
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• v.34 no.4
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• pp.1335-1352
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• 2019

In this article, a new family of lifetime distributions by adding two additional parameters is introduced. The new family is called, the logarithmic Kumaraswamy family of distributions. For the proposed family, explicit expressions for some mathematical properties are derived. Maximum likelihood estimates of the model parameters are also obtained. This method is applied to develop a new lifetime model, called the logarithmic Kumaraswamy Weibull distribution. The proposed model is very flexible and capable of modeling data with increasing, decreasing, unimodal or modified unimodal shaped hazard rates. To access the behavior of the model parameters, a simulation study has been carried out. Finally, the potentiality of the new method is proved via analyzing two real data sets.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.68 no.1
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• pp.52-60
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• 2019

In this paper, four types of insulation coils were fabricated by adding various kinds of glycols to improve the flexibility and adhesion of insulating coils in varnish dispersed with PAI / Nano Silica_15wt%. The applied voltage and frequency were 1.5 kV / 20 kHz for accelerated life evaluation. Through the 6th temperature stress level, the cause of the insulation breakdown of the coil was ignored and only the breakdown time was measured. The Arrhenius model was chosen based on the theoretical relationship between chemical reaction rate and temperature for estimating the insulation life of the coil due to accelerated thermal stress. Three types of distributions (Weibull, Lognormal, Exponential) were selected as the relationship between thermal stress model and distribution. The average insulation lifetime was estimated under the temperature stress of four types of insulation coils through the relationship between one kind of model and three kinds of distributions.

• Proceedings of the Korean Society for Quality Management Conference
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• 1998.11a
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• pp.544-555
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• 1998

Although the bimodal mixed weibull distribution is used to developing burn-in model widely, the failure times for a component or a system is often truncated at some time, T, due to the obsolescence in the electronics industry. In this paper, we will determine minimum total cost and burn-in time by using the bimodal mixed weibull distribution and the truncated bimodal mixed weibull distribution under the free warranty policy. The results of this study are summarized as follows. First, when products or system is not repairable, the width of the change of burn-in time can be larger by ${\beta}_1,\;{\beta}_2$ Second, if burn-in time become longer, it will be impossible to consider the bum-in in a long time, and in this case, the burn-in time should be shorten by the acceleration burn-in. Third, in case that opportunity loss cost or repair cost is exceed the warranty cost, or the total cost of considering burn-in is larger than that of not considering burn-in, it is not existed burn-in time which makes total cost to minimize. Forth, the shorter life-cycle of product, the more burn-in times will be decreased and the cost in considering burn-in will be increased

• Communications for Statistical Applications and Methods
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• v.31 no.1
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• pp.55-64
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• 2024

In this study, we consider the sample size determination problem for clustered count data with many zeros. In general, zero-inflated Poisson and binomial models are commonly used for zero-inflated data; however, in real data the assumptions that should be satisfied when using each model might be violated. We calculate the required sample size based on a discrete Weibull regression model that can handle both underdispersed and overdispersed data types. We use the Monte Carlo simulation to compute the required sample size. With our proposed method, a unified model with a low failure risk can be used to cope with the dispersed data type and handle data with many zeros, which appear in groups or clusters sharing a common variation source. A simulation study shows that our proposed method provides accurate results, revealing that the sample size is affected by the distribution skewness, covariance structure of covariates, and amount of zeros. We apply our method to the pancreas disorder length of the stay data collected from Western Australia.

• Journal of Advanced Research in Ocean Engineering
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• v.4 no.4
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• pp.185-194
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• 2018

In this study, the extreme sloshing pressure was predicted using various statistical models: three-parameter Weibull distribution, generalized Pareto distribution, generalized extreme value distribution, and three-parameter log-logistic distribution. The estimation of sloshing impact pressure is important in design of liquid cargo tank in severe sea state. In order to get the extreme values of local impact pressures, a lot of model tests have been carried out and statistical analysis has been performed. Three-parameter Weibull distribution and generalized Pareto distribution are widely used as the statistical analysis method in sloshing phenomenon, but generalized extreme value distribution and three-parameter log-logistic distribution are added in this study. Additionally, statistical distributions are fitted to peak pressure data using three different parameter estimation methods. The data were obtained from a three-dimensional sloshing model text conducted at Seoul National University. The loading conditions were 20%, 50%, and 95% of tank height, and the analysis was performed based on the measured impact pressure on four significant panels with large sloshing impacts. These fittings were compared by observing probability of exceedance diagrams and probability plot correlation coefficient test for goodness-of-fit.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.10
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• pp.1281-1289
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• 2011

This paper deals with several statistical distribution functions for the analysis of fatigue life data of composite laminates for small wind-turbine blades. A series of tensile tests was performed on triaxial glass/epoxy laminates for loading directions of $0^{\circ}$, $45^{\circ}$, and $90^{\circ}$. Then, fatigue tests were carried out to determine the fatigue life at the aforementioned loading directions and the fatigue stresses at four levels. Two-parameter Weibull, three-parameter Weibull, normal, and log-normal distributions were used to fit the fatigue life data of the triaxial composite laminates. The three-parameter Weibull distribution most accurately described the fatigue life data measured experimentally for all the cases considered. Furthermore, the variation of fatigue life was simultaneously affected by the loading direction and fatigue stress level.

• Journal of the Korean Statistical Society
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• v.28 no.4
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• pp.415-433
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• 1999

This paper considers the design of step-stress accelerated life tests for the Weibull distribution with a nonconstant shape parameter under Type I censoring. It is assumed that scale and shape parameters are log-linear functions of (possibly transformed) stress and that a cumulative exposure model holds for the effect of changing stress. The asymptotic variance of the maximum likelihood estimator of a stated quantile at design stress is used as an optimality criterion. The optimum three step-stress plans are presented for selected values of design parameters and the effects of errors in pre- estimates of the design parameters are investigated.

• Journal of Applied Reliability
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• v.14 no.1
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• pp.45-51
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• 2014

Thermal shock tests at two stress levels were performed to see the life (cycles) of LPF ASSY (low pass filter assembly) at normal stress level. In this case Coffin-Manson relationship is generally used to describe the relationship between the temperature difference and the life, together with the Weibull distribution describing the life at each stress level. So for given data Coffin-Manson is fitted to predict the life at normal stress level. However, different types of models are appropriate for this type of test. Hence, a more appropriate model such as General log-linear model which can also incorporate the duration at the highest and lowest temperatures and acceleration time will be introduced.