• Journal of Korean Society of Water and Wastewater
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• v.26 no.2
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• pp.321-329
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• 2012

In this study, statistical analysis under both stationary and non-stationary climate was conducted for rainfall data measured in Seoul. Generalised Extreme Value (GEV) distribution and Gumbel distribution were used for the analysis. Rainfall changes under the non-stationary climate were estimated by applying time variable (t) to location parameter (${\xi}$). Rainfall depths calculated in non-stationary climate increased by 1.1 to 6.2mm and 1.0 to 4.6mm for the GEV distribution and gumbel distribution respectively from those stationary forms. Changes in annual maximum rainfall were estimated with rate of change in the location parameter (${\xi}1{\cdot}t$), and temporal changes of return period were predicted. This was also available for re-evaluating the current sewer design return period. Design criteria of sewer system was newly suggested considering life expectance of the system as well as temporal changes in the return period.

• Transactions of the Korean Society of Mechanical Engineers
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• v.14 no.1
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• pp.138-144
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• 1990

In order to understand the probabilistic nature of fatigue crack propagation, not only the calculation of failure probability and parameter sensitivity, but also the clarification of probabilistic nature of various parameters should be executed. Therefore a method to evalute synthetically the effect of each parameter on the distribution of fatigue crack propagation life is required. In this study, the effects of the initial crack size and other paramaters on the distribution of fatigue crack propagation life are discussed according to the appropriate normalization of the life distribution, the validity of this method is also shown. Such an investigation as the present work may be useful to understand the nature of the life distribution and to utilize the probailistic fracture mechanics.

• Proceedings of the Korea Committee for Ocean Resources and Engineering Conference
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• 2002.05a
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• pp.104-109
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• 2002

In this paper, a statistical analysis of fatigue crack growth behavior under constant amplitude loads has been carried out. Fatigue crack growth tests were conducted on sixteen pre-cracked compact tension (CT) specimens of the pressure vessel (SPV50) steel in controlled identical load and environmental conditions. The assessment of the statistical distribution of fatigue crack growth experimental data obtained from SPV50 steel was studied and also the correlation of the parameter C and m in the Paris-Erdogan law was discussed. The probability distribution function of fatigue crack growth life seems to follow the 3-parameter Weibull. The fatigue crack growth rate seems to follow the 3-parameter Weibull and the log-normal distribution. The coefficient of variation (COV) of fatigue crack growth life was observed to decrease as the crack grows. A strong negative linear correlation exists between the coefficient C and the exponent m in Paris model. Fatigue crack growth rate data shows a normal distribution for both m and logC.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.27 no.6
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• pp.923-929
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• 2003

In this paper, an analysis of fatigue crack growth behavior from a statistical point of view has been carried out. Fatigue crack growth tests were conducted on sixteen pre-cracked compact tension (CT) specimens of the pressure vessel (SPV50) steel in controlled identical load and environmental conditions. The assessment of the statistical distribution of fatigue crack growth experimental data obtained from SPV50 steel was studied and also the correlation of the parameter C and m in the Paris-Erdogan law was discussed. The probability distribution function of fatigue crack growth life seems to follow the 3-parameter Weibull. The fatigue crack growth rate seems to follow the 3-parameter Weibull and the log-normal distribution. The coefficient of variation (COV) of fatigue crack growth life was observed to decrease as the crack grows. Fatigue crack growth rate data shows a normal distribution for both m and logC. A strong negative linear correlation exists between the coefficient C and the exponent m.

• Journal of the Korean Wood Science and Technology
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• v.31 no.3
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• pp.61-69
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• 2003

This study investigated the effect of moisture content and loading direction on dowel bearing strength of two types of SCL. Dowel bearing tests of LVL and PSL were conducted with two different MC level, 7.5% and 19%, and two different oriention, L-direction(loading parallel to grain) and X-direction(loading perpendicular to grain). Most of specimens showed typical load-deformation curves and intersected 5% offset line. Failure modes were classified into two categories; spliting(for L-direction specimens) and peeling(for X-direction specimens). Dowel bearing strength generally decreased with increasing MC. The decreasing rate was more significant in X-directon. ESG also decreased with increasing MC, and the ratio of ESG of 7.5% versus 19% was about 1.47. Dowel bearing strength of LVL and PSL in L-direction was higher than that of X-direction. This results indicated that MC and loading orientation had a significant effect on dowel bearing strength of SCL. The average dowel bearing strength of LVL were higher than that of PSL in each loading direction. Two types of probability distribution model were chosen to quantify strength distribution, normal and 2-parameter weibull distribution. The two models showed good agreement with the data, especially in lower tail of the cumulative distribution. Normal and 2-parameter weibull distribution seemed to proper model of the dowel bearing strength for each MC levels.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.1
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• pp.15-24
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• 2006

In simulation input modeling, it is important to identify a probability distribution to represent the input process of interest. In this paper, an appropriate sample size is determined for parameter estimation associated with some typical probability distributions frequently encountered in simulation input modeling. For this purpose, a statistical measure is proposed to evaluate the effect of sample size on the precision as well as the accuracy related to the parameter estimation, square rooted mean square error to parameter ratio. Based on this evaluation measure, this sample size effect can be not only analyzed dimensionlessly against parameter's unit but also scaled regardless of parameter's magnitude. In the Monte Carlo simulation experiments, three continuous and one discrete probability distributions are investigated such as ; 1) exponential ; 2) gamma ; 3) normal ; and 4) poisson. The parameter's magnitudes tested are designed in order to represent distinct skewness respectively. Results show that ; 1) the evaluation measure drastically improves until the sample size approaches around 200 ; 2) up to the sample size about 400, the improvement continues but becomes ineffective ; and 3) plots of the evaluation measure have a similar plateau pattern beyond the sample size of 400. A case study with real datasets presents for verifying the experimental results.

• Journal of the Korean Data and Information Science Society
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• v.14 no.4
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• pp.799-803
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• 2003

We obtained the best linear unbiased estimator for the scale parameter of the generalized Pareto Distribution by the order statistics.

• Wind and Structures
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• v.22 no.4
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• pp.393-408
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• 2016

Weibull distribution is a suitable distribution to use in modeling the life time data. It has been found to be a exact fit for the empirical distribution of the wind speed measurement samples. In brief this paper consist of important properties and characters of Weibull distribution. Also we discuss the application of Weibull distribution to wind speed measurements and derive an expression for the probability distribution of the power produced by a wind turbine at a fixed location, so that the modeling problem reduces to collecting data to estimate the three parameters of the Weibull distribution using Maximum likelihood Method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.11 s.254
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• pp.1417-1424
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• 2006

In order to evaluate variation of fatigue life of mechanical components including engineering plastics, it is important to estimate probabilistic strain-life curves to accurately define the variation of fatigue characteristics. This paper intends to provide new assessment of P-$\varepsilon$-N (probabilistic strain-life curves) for considering the variation of fatigue characteristics in polyacetal. The fatigue strain controlled tests were conducted under constant 50% humidity and room temperature condition by a universal testing machine at strain ratio, R=0. A practical procedure is introduced to evaluate probabilistic strain-life curves. Three probabilistic distributions were used for generating P-$\varepsilon$-N curves such as normal, 2-parameter and 3-parameter Weibull. In this study, 3-parameter Weibull distribution was found to be most appropriate among assumed distributions when the probability distributions of the fatigue characteristic were examined using chi-square and Kolmogorov-Smirnov test. The more appropriate P-$\varepsilon$-N curves for these materials are generated by the proposed method considering 3-parameter Weibull distribution.

• Journal of Advanced Marine Engineering and Technology
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• v.28 no.6
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• pp.993-999
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• 2004

The estimation of fatigue life at the design stage of membrane type LNG tank is very important in order to arrive at feasible and cost effective solutions considering the total lifetime of the tank. In this study, the practical procedure of fatigue life prediction by use of cumulative damage factors based on Miner-Palmgren hypothesis and probability density function has been shown with the corner region of Gaz Transport Membrane type LNG tank being used as an example. In particular the parameters of Weibull distribution that determine the stress spectrum are discussed. The main results obtained from this study are as follows: 1. The recommended value for the shape parameter of Weibull distribution for the LNG tank is 1.1 in case of using the direct calculation method proposed in this study. 2. The calculated fatigue life is influenced by the shape parameter of Weibull distribution and stress block. The safe fatigue design can be achieved by using higher value of shape parameter and the stress blocks divided into more stress blocks.