• Journal of Korean Society of Coastal and Ocean Engineers
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• v.28 no.2
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• pp.92-100
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• 2016

Reliability analysis of tripod support structure for offshore wind turbine was performed. Extreme distribution function of peak response due to wind and wave loads was estimated by applying peak over threshold(POT) method. Then, stress based limit state function was defined by using maximum stress of support structure which was obtained by multiplying beam stress and concentration factor. The reliability analysis result was compared when maximum stress was calculated from shell element. Reliability index was evaluated using first order reliability method(FORM).

• International Journal of Naval Architecture and Ocean Engineering
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• v.12 no.1
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• pp.657-666
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• 2020

A reliable and cost-effective technique for the development of corrosion damage model is introduced to predict nonlinear time-dependent corrosion wastage of steel structures. A detailed explanation on how to propose a generalised mathematical formulation of the corrosion model is investigated in this paper (Part I), and verification and application of the developed method are covered in the following paper (Part II) by adopting corrosion data of a ship's ballast tank structure. In this study, probabilistic approaches including statistical analysis were applied to select the best fit probability density function (PDF) for the measured corrosion data. The sub-parameters of selected PDF, e.g., the largest extreme value distribution consisting of scale, and shape parameters, can be formulated as a function of time using curve fitting method. The proposed technique to formulate the refined time-dependent corrosion wastage model (TDCWM) will be useful for engineers as it provides an easy and accurate prediction of the 1) starting time of corrosion, 2) remaining life of the structure, and 3) nonlinear corrosion damage amount over time. In addition, the obtained outcome can be utilised for the development of simplified engineering software shown in Appendix B.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.25 no.4
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• pp.191-199
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• 2013

It is estimated and analyzed that the design wave height and the confidence interval (hereafter CI) according to the return period using the fourteen-year wave data obtained at Pusan New Port. The functions used in the extreme value analysis are the Gumbel function, the Weibull function, and the Kernel function. The CI of the estimated wave heights was predicted using one of the Monte-Carlo simulation methods, the Bootstrap method. The analysis results of the estimated CI of the design wave height indicate that over 150 years of data is necessary in order to satisfy an approximately ${\pm}$10% CI. Also, estimating the number of practically possible data to be around 25~50, the allowable error was found to be approximately ${\pm}$16~22% for Type I PDF and ${\pm}$18~24% for Type III PDF. Whereas, the Kernel distribution method, a typical non-parametric method, shows that the CI of the method is below 40% in comparison with the CI of the other methods and the estimated design wave height is 1.2~1.6 m lower than that of the other methods.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.10 no.4
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• pp.204-210
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• 1998

This paper presents the development of the probability density function applicable for wave heights (peak-to-trough excursions) in finite water depth including shallow water depth. The probability distribution applicable to wave heights of a non-Gaussian random process is derived based on the concept of the maximum entropy method. When wave heights are limited by breaking wave heights (or water depth) and only first and second moments of wave heights are given, the probability density function developed is closed form and expressed in terms of wave parameters such as $H_m$(mean wave height), $H_{rms}$(root-mean-square wave height), $H_b$(breaking wave height). When higher than third moment of wave heights are given, it is necessary to solve the system of nonlinear integral equations numerically using Newton-Raphson method to obtain the parameters of probability density function which is maximizing the entropy function. The probability density function thusly derived agrees very well with the histogram of wave heights in finite water depth obtained during storm. The probability density function of wave heights developed using maximum entropy method appears to be useful in estimating extreme values and statistical properties of wave heights for the design of coastal structures.

• The Korean Journal of Applied Statistics
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• v.24 no.5
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• pp.931-939
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• 2011

In practice, thresholds are determined by the two subjective assessment methods in a generalized pareto distribution of mean extreme function(MEF-graph) or Hill-graph. To remedy the problem of subjectiveness of these methods, we propose an alternative method to determine the threshold based on the robust statistics. We compared the MEF-graph, Hill-graph and our method through VaRs on the Korean stock market data from January 5, 1987 to August 3, 2009. As a result, the VaR based on the proposed method is not much different from the existing methods, and the standard deviation of VaR for our method was the smallest. The results show that our method can be a promising alternative to determine thresholds of the generalized pareto distributions.

• Journal of Korea Water Resources Association
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• v.47 no.11
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• pp.985-996
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• 2014

When designing hydraulic structures, the chosen method of time distribution in a hyetograph is highly significant. There are several methods used for measuring time distribution. In the case of Huff (1967), which is widely used in Korea, the Ministry of Construction and Transportation (MOCT, 2000), and the Ministry of Land, Transport and Maritime Affairs (MOLTMA, 2011) have long been increasing their use of this method. The MOLTMA uses the conventional Huff method's measurement of 1 inch (25.4 mm) as the threshold. Many researchers have pointed out that this method often leads to underestimation, because of the excessive flatness. Therefore, for this study, a new time distribution method was developed to analyze only extreme rainfall events-those over the standard of severe rainstorms (that is, more than 30 mm per hour or 80 mm per day)-and that was verified using a rainfall-runoff model and applying it to a real basin.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3A
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• pp.199-207
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• 2009

In this paper, new vehicular load model is developed for reliability-based bridge design code. Rational load model and statistical properties of loads are important for developing reliability-based design code. In the previous paper, truck weight data collected at eight locations using WIM or BWIM system are analyzed to calculate the maximum truck weights for specified bridge lifetime. Probability distributions of upper 20% total truck weight are assumed as Extreme Type I (Gumbel Distribution) and 100 years maximum weights are estimated by linear regression. In this study, effects of multiple presence of trucks are analyzed. Probability of multiple presence of trucks are estimated and corresponding multiple truck weights are calculated using the same probability distribution function as in the previous paper. New vehicular live load model are proposed for span length from 10 m to 200 m. New model is compared with current Korean model and various load models of other countries.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.152-152
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• 2022

Only employing historical data limits the estimation of the full distribution of probable Tropical Cyclone (TC) risk due to the insufficiency of samples. Addressing this limitation, this study introduces a semi-physical TC rainfall model that produces spatially and temporally resolved TC rainfall data to improve TC risk assessments. The model combines a statistical-based track model based on the Markov renewal process to produce synthetic TC tracks, with a physics-based model that considers the interaction between TC and the atmospheric environment to estimate TC rainfall. The simulated data from the combined model are then fitted to a probability distribution function to compute the spatially heterogeneous risk brought by landfalling TCs. The methodology is employed in South Korea as a case study to be able to implement a country-scale-based vulnerability inspection from damaging TC impacts. Results show that the proposed model can produce TC tracks that do not only follow the spatial distribution of past TCs but also reveal new paths that could be utilized to consider events outside of what has been historically observed. The model is also found to be suitable for properly estimating the total rainfall induced by landfalling TCs across various points of interest within the study area. The simulated TC rainfall data enable us to reliably estimate extreme rainfall from higher return periods that are often overlooked when only the historical data is employed. In addition, the model can properly describe the distribution of rainfall extremes that show a heterogeneous pattern throughout the study area and that vary per return period. Overall, results show that the proposed approach can be a valuable tool in providing sufficient TC rainfall samples that could be an aid in improving TC risk assessment.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.4B
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• pp.319-328
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• 2009

This study quantified the data by applying the EDA techniques considering the data structure, and the results were then used for the frequency analysis. Although traditional methods based on the method of moments provide very sensitive statistics to the extreme values, the EDA techniques have an advantage of providing very stable statistics with their small variation. For the application of the EDA techniques to the frequency analysis, it is necessary to normalization transform and inverse-transform to conserve the skewness of the raw data. That is, it is necessary to transform the raw data to make the data follow the normal distribution, to estimate the statistics by applying the EDA techniques, and then finally to inverse-transform the statistics of transformed data. These statistics decided are then applied for the frequency analysis with a given probability density function. This study analyzed the annual maxima one hour rainfall data at Seoul and Pohang stations. As a result, it was found that more stable rainfall quantiles, which were also less sensitive to extreme values, could be estimated by applying the EDA techniques. This methodology may be effectively used for the frequency analysis of rainfall at stations with especially high annual variations of rainfall due to climate change, etc.

• Journal of Korean Society of Disaster and Security
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• v.6 no.2
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• pp.1-8
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• 2013

This study is concerned with the estimation of fluctuate wind velocity statistic properties in the major cities reflecting the recent meteorological with largest data samples (yearly 2003-2012). The basic wind speeds were standardized homogeneously to the surface roughness category C, and to 10m above the ground surface. The estimation of the extreme of non-Gaussian load effects for design applications has often been treated tacitly by invoking a conventional wind design (gust load peak factor) on the basis of Gaussian processes. This assumption breaks down when the loading processes exhibits non-Gaussianity, in which a conventional wind design yields relatively non conservative estimates because of failure to include long tail regions inherent to non-Gaussian processes. This study seeks to ascertain the probability distribution function from recently wind data with effected typhoon & maximum instantaneous wind speed.