• Journal of the Korean Data and Information Science Society
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• 제26권2호
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• pp.535-545
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• 2015

In a various range of applications including hydrology, the type-I extreme value distribution has been extensively used as a probabilistic model for analyzing extreme events. In this paper, we introduce methods for estimating the scale parameter of the type-I extreme value distribution. A simulation study is performed to compare the estimators in terms of mean-squared error and bias, and the obtained results are provided.

• Journal of the Korean Data and Information Science Society
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• 제25권3호
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• pp.643-653
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• 2014

In this paper, we propose some estimators for the extreme value distribution based on the interval method and mid-point approximation method from the progressive Type-I interval censored sample. Because log-likelihood function is a non-linear function, we use a Taylor series expansion to derive approximate likelihood equations. We compare the proposed estimators in terms of the mean squared error by using the Monte Carlo simulation.

• Wind and Structures
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• 제9권3호
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• pp.179-191
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• 2006

Parent wind data are often acknowledged to fit a Weibull probability distribution, implying that wind epoch maxima should fall into the domain of attraction of the Gumbel (Type I) extreme value distribution. However, observations of wind epoch maxima are not fitted well by this distribution and a Generalised Extreme Value (GEV) analysis leading to a Type III fit empirically appears to be better. Thus there is an apparent paradox. The reasons why advocates of the GEV approach seem to prefer it are briefly summarised. This paper gives a detailed analysis of the errors involved when the GEV is fitted to epoch maxima of Weibull origin. It is shown that the results in terms of the shape parameter are an artefact of these errors. The errors are unavoidable with the present sample sizes. If proper significance tests are applied, then the null hypothesis of a Type I fit, as predicted by theory, will almost always be retained. The GEV leads to an unacceptable ambiguity in defining design loads. For these reasons, it is concluded that the GEV approach does not seem to be a sensible option.

• Wind and Structures
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• 제19권5호
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• pp.467-480
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• 2014

The estimation of wind speed values used in codes and standards is an integral part of the wind load evaluation process. In a number of codes and standards, wind speeds outside of tropical cyclone prone regions are estimated using a single probability distribution developed from observed wind speed data, with no distinction made between the types of causal wind hazard (e.g., thunderstorm). Non-tropical cyclone wind hazards (i.e., thunderstorm, non-thunderstorm) have been shown to possess different probability distributions and estimation of non-tropical cyclone wind speeds based on a single probability distribution has been shown to underestimate wind speeds. Current treatment of non-tropical cyclone wind hazards in worldwide codes and standards is touched upon in this work. Meteorological data is available at a considerable number of United States (U.S.) stations that have information on wind speed as well as the type of causal wind hazard. In this paper, probability distributions are fit to distinct storm types (i.e., thunderstorm and non-thunderstorm) and the results of these distributions are compared to fitting a single probability distribution to all data regardless of storm type (i.e., co-mingled). Distributions fitted to data separated by storm type and co-mingled data will also be compared to a derived (i.e., "mixed") probability distribution considering multiple storm types independently. This paper will analyze two extreme value distributions (e.g., Gumbel, generalized Pareto). It is shown that mixed probability distribution, on average, is a more conservative measure for extreme wind speed estimation. Using a mixed distribution is especially conservative in situations where a given wind speed value for either storm type has a similar probability of occurrence, and/or when a less frequent storm type produces the highest overall wind speeds. U.S. areas prone to multiple non-tropical cyclone wind hazards are identified.

• Nuclear Engineering and Technology
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• 제54권5호
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• pp.1606-1615
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• 2022

For investigating whether the MARSSIM nonparametric test has sufficient statistical power when a site has a specific contamination distribution before conducting a final status survey (FSS), a novel approach was proposed to predict the release probability of the site. Five distributions were assumed: lognormal distribution, normal distribution, maximum extreme value distribution, minimum extreme value distribution, and uniform distribution. Hypothetical radioactivity populations were generated for each distribution, and Sign tests were performed to predict the release probabilities after extracting samples using Monte Carlo simulations. The designed Type I error (0.01, 0.05, and 0.1) was always satisfied for all distributions, while the designed Type II error (0.01, 0.05, and 0.1) was not always met for the uniform, maximum extreme value, and lognormal distributions. Through detailed analyses for lognormal and normal distributions which are often found for contaminants in actual environmental or soil samples, it was found that a greater statistical power was obtained from survey units with normal distribution than with lognormal distribution. This study is expected to contribute to achieving the designed decision error when the contamination distribution of a survey unit is identified, by predicting whether the survey unit passes the statistical test before undertaking the FSS according to MARSSIM.

• Journal of Electrical Engineering and information Science
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• 제1권1호
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• pp.45-50
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• 1996

This paper mainly describes the wind load assumption of 765kV transmission towers. We analyzed wind velocity data a meteorological observatories to get the wind velocity of 50 years return period by using Gumbel I type extreme value distribution. By multi-correlative regression analysis method, wind velocity at no observation site was obtained. Reference dynamics wind pressure map was obtained from above analysis and the wind pressure was classified as three regio in high temperature season.

• Steel and Composite Structures
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• 제3권3호
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• pp.185-198
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• 2003

The concept of performance based seismic design has been gradually accepted by the earthquake engineering profession recently, in which the cost-effectiveness criterion is one of the most important principles and more attention is paid to the structural performance at the inelastic stage. Since there are many uncertainties in seismic design, reliability analysis is a major task in performance based seismic design. However, structural reliability analysis may be very costly and time consuming because the limit state function is usually a highly nonlinear implicit function with respect to the basic design variables, especially for the complex large-scale structures for dynamic and nonlinear analysis. Understanding statistical properties of the structural inelastic deformation, which is the aim of the present paper, is helpful to develop an efficient approximate approach of reliability analysis. The present paper studies the statistical properties of the maximum elastoplastic story drift of steel frames subjected to earthquake load. The randomness of earthquake load, dead load, live load, steel elastic modulus, yield strength and structural member dimensions are considered. Possible probability distributions for the maximum story are evaluated using K-S test. The results show that the choice of the probability distribution for the maximum elastoplastic story drift of steel frames is related to the mean value of the maximum elastoplastic story drift. When the mean drift is small (less than 0.3%), an extreme value type I distribution is the best choice. However, for large drifts (more than 0.35%), an extreme value type II distribution is best.

• 한국해안해양공학회지
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• 제16권3호
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• pp.130-141
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• 2004

연안 및 항만구조물의 설계에서 심해 설계파는 매우 중요한 환경인자이다. 특히, 심해설계파고의 분포 정보는 최근 부각되고 있는 신뢰성 설계에 필수적인 요소이다. 본 연구에서는 한국해양연구원(2003)에서 제시한 1979년부터 1998년까지의 한국연안 67개 지점의 16방향별 최대 유의파 산출자료를 이용하여 극치분포 분석을 수행하였다. 특성분석에 사용된 극치분포함수는 Weibull, Gumbel, Log-Pearson Type-III, Lognormal 분포이며, 각 분포함수의 매개변수는 모멘트법, 최우도법 그리고 확률가중모멘트법으로 추정하였다. 또한, 극치분포함수의 적합성은 95% 신뢰도 수준으로 $\chi$$^2$및 K-S 검정을 실시하였다. 그 결과, 한국연안의 심해 설계파고는 Gumbel 분포형이 가장 적합한 모형으로 파악되었으며, 최적 추정된 매개변수 및 재현기간 50년에 대한 심해 설계파고 정보를 제시하였다.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2005년도 춘계학술대회 논문집
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• pp.245-251
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• 2005

연안 및 항만시설물의 설계에서 심해 설계파 및 풍속은 매우 중요한 설계 파라메타이다. 특히, 최근 부각되고 있는 방재공학 측면에서 이러한 정보에 대한 분석단계는 필수적이라 할 수 있다. 본 연구에서는 완도관측소의 기상연보에서 제시한 1978년부터 2003년까지의 풍속자료와 한국해양연구원 파랑정보시스템에서 제공하는 16방향별 최대 유의파 산출자료를 이용하여 극치분석을 수행하였다. 특성분석에 사용된 극치분포함수는 Weibull, Gumbel, Log-Pearson Type-III, Normal, Lognormal, Gamma 분포이며, 각 분포함수의 매개변수는 모멘트법, 최우도법 그리고 확률 가중 모멘트법으로 추정하였다. 또한, 극치분포함수의 적함성은 5${\%}$의 유의수준 즉, 95${\%}$신뢰도 수준으로 $x^{2}$및 K-S 검정을 실시하였다. 그 결과, 한국 남서연안의 심해 설계파고는 Gumbel 분포형이 가장 적합한 모형으로 파악되었으나, 본 연구의 대상영역에 적합한 모형은 각각의 극치자료에 따라 선정된 확률분포에 의해 다르게 나타났다.

• Wind and Structures
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• 제37권2호
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• pp.153-161
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• 2023

Wind speed data from Nepal and adjoining countries have been analyzed to estimate an extreme wind speed climatology for the region. Previously wind speed information for Nepal was adopted from the Indian National Standard and applied to two orographically different regions: above and below 3000 m elevation respectively. Comparisons of the results of this analysis are made with relevant codes and standards. The study confirms that the assigned basic wind speed of 47 m/s for the plains and hills of Nepal (below 3000 m) is appropriate, however, data to substantiate a basic wind speed of 55 m/s above 3000 m is unavailable. Using a composite analysis of 15 geographically similar stations, the study also generated 435 years of annual maxima wind data and fitted them to Type I and Type III extreme value distributions. The results suggest that Type III distribution may better represent the data. The findings are also consistent with predictions made by Holmes and Weller (2002) and to a certain extent those of Sarkar et al. (2014), but lower than the analysis undertaken by Lakshmanan et al. (2009) for northern India. The study also highlights that the use of a load factor of 1.5 on wind load implies lower strength design MRI's of around 260 years compared to the 700 years of ASCE 7-22.