• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1994.10a
• /
• pp.815-819
• /
• 1994

In this paper, the tensile strength in aluminum alloy 5052, Kevlar 49-fiber reinforced aluminum alloy laminates, and Glass-fiber reinforced aluminum alloy laminates, is statistically evaluated. Prepregs manufactured in Han Kuk Fiber is used and FRMLs is cured by Hot-Press. Standard statistical are used to determine the distribution function which best fits FRMLs strength data. The normal,lpg-normal, and two-parameter Weibull distrbuttion are evaluated using the Kolmogoorov-Smirnov goodness-of-fit test. At the 5% significance level, none of these distribution is rejected. The strength of Aluminum alloy 5052 is best fits to a normal distribution. However, the strength of Kevlar 49-fiber reinforced aluminum alloy laminates and Glass-fiber reinforced aluminum alloy laminates is best fits to a two-parameter Weibull distribution.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.33 no.5
• /
• pp.1731-1740
• /
• 2013

The design life and durability of the bridges are strongly affected by the Gross Vehicle Weight(GVW) of heavyweight trucks. The Weigh-In-Motion(WIM) systems are typically used to collect information on truck total weight and speed. The statistical analysis of the GVW measured using High Speed WIM systems showed that most of heavy vehicles were from Vehicle Type 7, 10, and 12. The analysis was also carried out to determine goodness of fit with theoretical probability distributions. The normal distribution was shown to best describe the overall distribution of GVW. The top 10% of the GVW appeared to best fit by the Weibull 3 probability distribution.

• Transactions of the Korean Society of Mechanical Engineers A
• /
• v.33 no.8
• /
• pp.707-719
• /
• 2009

The variables relating to the fatigue behavior have uncertainty and are random. The fatigue crack propagation is, thus, stochastic in nature. In this study, fatigue experiments are performed on the specimen of the magnesium alloy AZ31. The data of the fatigue life are scattered even in the same experimental condition. It is necessary to determine the probability distribution of the fatigue crack propagation life for the reliability analysis as well as the design and maintenance of structural components. Therefore the statistics and the probability distribution for the fatigue crack propagation life are investigated and the best fit probability distribution of that is proposed in this paper.

• Journal of the Korean Society of Manufacturing Technology Engineers
• /
• v.18 no.5
• /
• pp.536-543
• /
• 2009

In this paper the mean stress effects on the probability distribution of the random grown crack size at a specified loading cycle are studied through the fatigue crack propagation tests, which are conducted on the specimens of magnesium alloy under four different stress ratios. Through 80 replicates the probability distributions of the grown crack size are obtained. The goodness-of-fit for probability distributions of the random grown crack size are investigated by Anderson-Darling test and the best fit for those probability distributions is found to be a 3-parameter Weibull distribution. The effects of the mean stress on the probability distribution of the random grown crack size are also estimated.

• Journal of Electrical Engineering and Technology
• /
• v.8 no.4
• /
• pp.840-849
• /
• 2013

This paper presents a statistical approach to analyze electrical tree inception voltage, electrical tree breakdown voltage and tree breakdown time of unsaturated polyester resin subjected to AC voltage. The aim of this work was to show that Weibull and lognormal distribution may not be the most suitable distributions for analysis of electrical treeing data. In this paper, an investigation of statistical distributions of electrical tree inception voltage, electrical tree breakdown voltage and breakdown time data was performed on 108 leaf-like specimen samples. Revelations from the test results showed that Johnson SB distribution is the best fit for electrical tree inception voltage and tree breakdown time data while electrical tree breakdown voltage data is best suited with Wakeby distribution. The fitting step was performed by means of Anderson-Darling (AD) Goodness-of-fit test (GOF). Based on the fitting results of tree inception voltage, tree breakdown time and tree breakdown voltage data, Johnson SB and Wakeby exhibit the lowest error value respectively compared to Weibull and lognormal.

• Korean Journal of Agricultural and Forest Meteorology
• /
• v.12 no.2
• /
• pp.83-94
• /
• 2010

The objective of this study was to determine the best probability distributions of annual, seasonal and monthly precipitation in Korea. Data observed at 32 stations in Korea were analyzed using the L-moment ratio diagram and the average weighted distance (AWD) to identify the best probability distributions of each precipitation. The probability distribution was best represented by 3-parameter Weibull distribution (W3) for the annual precipitation, 3-parameter lognormal distribution (LN3) for spring and autumn seasons, and generalized extreme value distribution (GEV) for summer and winter seasons. The best probability distribution models for monthly precipitation were LN3 for January, W3 for February and July, 2-parameter Weibull distribution (W2) for March, generalized Pareto distribution (GPA) for April, September, October and November, GEV for May and June, and log-Pearson type III (LP3) for August and December. However, from the goodness-of-fit test for the best probability distributions of the best fit, GPA for April, September, October and November, and LN3 for January showed considerably high reject rates due to computational errors in estimation of the probability distribution parameters and relatively higher AWD values. Meanwhile, analyses using data from 55 stations including additional 23 stations indicated insignificant differences to those using original data. Further studies using more long-term data are needed to identify more optimal probability distributions for each precipitation.

• International conference on construction engineering and project management
• /
• 2009.05a
• /
• pp.393-399
• /
• 2009

This paper introduces an automated tool named Advanced Stochastic Schedule Simulation System (AS4). The system automatically integrates CPM schedule data exported from Primavera Project Planner (P3) and historical activity duration data obtained from a project data warehouse, computes the best fit probability distribution functions (PDFs) of historical activity durations, assigns the PDFs identified to respective activities, computes the optimum number of simulation runs, simulates the schedule network for the optimum number of simulation runs, and estimates the best fit PDF of project completion times (PCTs). AS4 improves the reliability of simulation-based scheduling by effectively dealing with the uncertainties of the activities' durations, increases the usability of the schedule data obtained from commercial CPM software, and effectively handles the variability of the PCTs by finding the best fit PDF of PCTs. It is designed as an easy-to-use computer tool programmed in MATLAB. AS4 encourages the use of simulation-based scheduling because it is simple to use, it simplifies the tedious and burdensome process involved in finding the PDFs of the many activities' durations and in assigning the PDFs to the many activities of a new network under modeling, and it does away with the normality assumptions used by most simulation-based scheduling systems in modeling PCTs.

• Journal of the Korean Wood Science and Technology
• /
• v.31 no.5
• /
• pp.72-79
• /
• 2003

In reliability based design(RBD) method, the distribution characteristics of mechanical properties of material are basic input variable. Therefore, distribution type and parameters of mechanical properties should be determined accurately. Until now, the properties were derived from tests with small, clear specimens. However, the test conditions should emulate as nearly as possible the way in which the timber would be used in practice and the test results should, as closely as possible, reflect the structural end use conditions to which the timber products would be subjected. In this study, structural timbers (38mm by 140mm, 3.0m long) were graded by visual assessment of growth characteristics and defects. And then bending tests were conducted on 498 structural size timbers. For each grade, the distribution type and the parameters of mechanical properties were determined for each grade. For the determination of best-fit distribution type, comparing of square error between distribution types and KS test were conducted. Best-fit distribution type of bending strength(MOR) is weibull distribution for all grade. In case of MOE, normal distribution is best-fit.

• Journal of Korea Water Resources Association
• /
• v.53 no.10
• /
• pp.917-928
• /
• 2020

The purpose of this study is to find the appropriate probability distribution representing the size distribution of suspended cohesive sediment. Based on goodness-of-fit test for a significance level of 5% using the Kolmogorov-Smirnov test, it is found that the floc size distributions measured in laboratory experiment and field study show different results. In the case of sample data collected from field experiments, the Gamma distribution is the best fitting form. In the case of laboratory experiment results, the sample data shows the positively-skewed distribution and the GEV distribution is the best fitted. The lognormal distribution, which is generally assumed to be a floc size distribution, is not suitable for both field and laboratory results. By using 3-parameter lognormal distribution, it is shown that similar size distribution with floc size distribution can be simulated.

• Magazine of the Korean Society of Agricultural Engineers
• /
• v.24 no.1
• /
• pp.53-62
• /
• 1982

This study was attempted to find best fitted distribution and the equations for probable maximum flow with the evaluation of parameters by the method of moment for the rat- ional design of hydraulic structures in the annual exceedance series. Six subwatersheds were selected as studying basins along Geum River basin. The results obtained through this study were analyzed and summarized as follows. 1. Fitted probability distribution was showed in the order of Three Parameter Lognorm al, Type 1 Extremal, Exponential, Pearson Type III, and Log Pearson Type I distribu- tion as the results of x$^2$ goodness of fit test. 2. Kolmogorov-Smirnov test showed in the order of Three Parameter Lognormal, Exp- onential' Pearson Type III, Log Pearson Type III and Type 1 Extremal distribution for the fitted probability distribution. 3. It can be concluded that Three parameter Lognormal distribution is a best fitted one among some other distributions out of respect for each both tests. An Exponential distribution was proposed as a suitable one by Chow, V.T. showeci lower fittness than that of Three Parameter Lognormal in Geum River basin. 5. Probable flood flow equations followins the return periods for each station were obt- ained by Three Parameter Lognormal distribution. 6. It is urgently essential that best fitted probability distribution should be established for the annual exceedance series in the main river systems of Korea.