• 한국수자원학회논문집
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• 제43권11호
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• pp.967-976
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• 2010

우수관의 성능이 한계상태(performance limit state)에 도달할 확률을 정량적으로 산정할 수 있는 FORM(First-Order Reliability Model)의 AFDA(Approximate Full Distribution Approach) 신뢰성 모형을 개발하였다. 우수관망에서 각각의 관으로 유입하는 유량이 그 관의 허용 가능 배출량을 초과하여 성능한계상태에 도달할 때 이를 파괴상태(failure state)라 정의하여 신뢰함수를 수립하였다. 우수관거로의 유입량은 합리식, 유출량은 Manning의 공식을 적용하였다. 또한 신뢰성 해석을 위한 관련 확률변수들에 대한 통계적 특성과 분포함수에 대한 해석이 수행되었다. 강우자료의 불확실성 해석에서 우리나라 여러 중소도시에 대한 연 최대강우강도의 확률분포가 Gumbel 극치분포함수와 일치함을 확인하였다. 개발된 신뢰성 모형을 Y자형 우수관망에 적용하여 성능한계상태가 발생할 확률, 즉 파괴확률(probability of failure)을 정량적으로 산정하였다. Manning의 공식을 이용하여 우수관의 직경 변화에 따른 파괴확률의 거동특성을 분석하였다. 특히 문경과 대전의 50년 재현기간을 갖는 설계 강우강도에 대한 우수관의 파괴확률을 산정한 결과에 의하면, 관의 직경이 특정수치 이하일 경우 파괴확률이 급격히 커지는 것을 확인할 수 있었다. 이는 실제 우수관의 유효직경이 설계직경에 가깝도록 항상 관내 불순물을 제거하는 것이 파괴확률을 줄이는 최선의 방법임을 의미하는 것이다. 또한 우수관 시스템의 경우 여러 개의 관이 모여 하나의 관으로 흘러 들어가는 경우가 많으며 이 경우 다중파괴유형(multiple failure mode)을 적용하여 시스템이 파괴상태에 도달할 확률을 정량적으로 산정하였다. 본 연구에서 개발된 신뢰성 모형은 우수관의 운용, 관리, 감독은 물론 설계에 활용이 가능 할 것이다.

• Wind and Structures
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• 제25권3호
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• pp.261-282
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• 2017

The probabilistic information of directional extreme wind speeds is important for precisely estimating the design wind loads on structures. A new joint probability distribution model of directional extreme wind speeds is established based on observed wind-speed data using multivariate extreme value theory with the t-Copula function in the present study. At first, the theoretical deficiencies of the Gaussian-Copula and Gumbel-Copula models proposed by previous researchers for the joint probability distribution of directional extreme wind speeds are analysed. Then, the t-Copula model is adopted to solve this deficiency. Next, these three types of Copula models are discussed and evaluated with Spearman's rho, the parametric bootstrap test and the selection criteria based on the empirical Copula. Finally, the extreme wind speeds for a given return period are predicted by the t-Copula model with observed wind-speed records from several areas and the influence of dependence among directional extreme wind speeds on the predicted results is discussed.

• Wind and Structures
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• 제19권6호
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• pp.623-647
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• 2014

In this paper, a probability distribution which is consistent with the observed phenomenon at the roof corner and, also on other portions of the roof, of a low-rise building is proposed. The model is consistent with the choice of probability density function suggested by the statistical thermodynamics of open systems and turbulence modelling in fluid mechanics. After presenting the justification based on physical phenomenon and based on statistical arguments, the fit of alpha-stable distribution for prediction of extreme negative wind pressure coefficients is explored. The predictions are compared with those actually observed during wind tunnel experiments (using wind tunnel experimental data obtained from the aerodynamic database of Tokyo Polytechnic University), and those predicted by using Gumbel minimum and Hermite polynomial model. The predictions are also compared with those estimated using a recently proposed non-parametric model in regions where stability criterion (in skewness-kurtosis space) is satisfied. From the comparisons, it is noted that the proposed model can be used to estimate the extreme peak negative wind pressure coefficients. The model has an advantage that it is consistent with the physical processes proposed in the literature for explaining large fluctuations at the roof corners.

• 상하수도학회지
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• 제30권4호
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• pp.369-379
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• 2016

It was confirmed that the extreme value distribution model applies to probability of exceeding more than once a day monthly the facility capacities using data of daily maximum inflow rate for 7 wastewater treatment plant. The result of applying the extreme value model, A, D, E wastewater treatment plant has a problem compared to B, C, F, G wastewater treatment plant. but all the wastewater treatment plant has a problem except C, F wastewater treatment plant based 80% of facility capacity. In conclusion, if you make a standard in statistical aspects probability exceeding more than once a day monthly can be 'exceed day is less than a few times annually' or 'probability of exceeding more than once a day monthly is less than what percent'.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2010년도 학술발표회
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• pp.581-585
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• 2010

This study introduced a Bayesian based frequency analysis in which the statistical trend seasonal analysis for hydrologic extreme series is incorporated. The proposed model employed Gumbel and GEV extreme distribution to characterize extreme events and a fully coupled bayesian frequency model was finally utilized to estimate design rainfalls in Seoul. Posterior distributions of the model parameters in both trend and seasonal analysis were updated through Markov Chain Monte Carlo Simulation mainly utilizing Gibbs sampler. This study proposed a way to make use of nonstationary frequency model for dynamic risk analysis, and showed an increase of hydrologic risk with time varying probability density functions. In addition, full annual cycle of the design rainfall through seasonal model could be applied to annual control such as dam operation, flood control, irrigation water management, and so on. The proposed study showed advantage in assessing statistical significance of parameters associated with trend analysis through statistical inference utilizing derived posterior distributions.

• Communications for Statistical Applications and Methods
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• 제17권4호
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• pp.493-505
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• 2010

Developing a test for independence of random variables X and Y against the alternative has an important role in statistical inference. Kochar and Gupta (1987) proposed a class of tests in view of Block and Basu (1974) model and compared the powers for sample sizes n = 8, 12. In this paper, we evaluate Kochar and Gupta (1987) class of tests for testing independence against quadrant dependence in absolutely continuous bivariate Farlie-Gambel-Morgenstern distribution, via a simulation study for sample sizes n = 6, 8, 10, 12, 16 and 20. Furthermore, we compare the power of the tests with that proposed by G$\ddot{u}$uven and Kotz (2008) based on the asymptotic distribution of the test statistics.

• 한국수자원학회논문집
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• 제45권3호
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• pp.263-274
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• 2012

최근 다양한 기후변동성으로 인해 전 세계적으로 극한호우사상이 동시다발적으로 일어나고 있다. 우리나라의 극한호우사상은 주로 여름철 태풍으로 인한 호우와 국지성 집중호우에 의해서 발생한다. 극한호우사상에 대한 적절한 확률강우량을 추정하기 위해서, 본 연구에서는 연최대치일강우를 태풍으로 인한 강우와 집중호우로 인한 강우로 구분하여 확률적 거동을 고려하였다. 일반적인 강우빈도해석법은 연최대치강우가 단일 모집단을 이룬다고 가정하여 단일 분포함수를 적용하여 확률강우량을 추정하는 반면, 본 연구에서는 연최대치강우를 구성하는 두 가지 호우의 통계적 특성을 수문빈도해석에서 고려하기 위해, 혼합 분포함수를 적용하였다. 비교적 긴 관측강우자료를 보유한 15개 지점을 선정하여, 일강우량에 대한 확률강우량을 산정하고 비교분석을 실시하였다. 혼합 검벨분포모형에 의한 확률강우량은 단일 검벨분포함수를 적용한 확률강우량과 비교하여 지역에 따라 증감이 나타났으며, 이러한 결과는 홍수방어시스템의 계획 및 설계에서 유용한 정보를 제공할 것이다.

• 상하수도학회지
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• 제24권5호
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• pp.509-517
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• 2010

Statistical distribution of annual maximum rainfall intensity of 18 cities in Korea was analyzed and applied to the reliability model which can calculate the probability of performance failure of storm sewer. After the analysis, it was found that distribution of annual maximum rainfall intensity of 18 cities in Korea is well matched with Gumbel distribution. Rational equation was used to estimate the load and Manning's equation was used to estimate the capacity in reliability function to calculate the probability of performance failure of storm sewer. Reliability analysis was performed by developed model applying to the real storm sewer. It was found that probability of performance failure is abruptly increased if the diameter is smaller than certain size. Therefore, cleaning the inside of storm sewer to maintain the original diameter can be one of the best ways to reduce the probability of performance failure. In the present study, probability of performance failure according to accumulation of debris in storm sewer was calculated. It was found that increasing the amount of debris seriously decrease the capacity of storm sewer and significantly increase the probability of performance failure.

• Wind and Structures
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• 제34권6호
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• pp.469-482
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• 2022

The generalized extreme value distribution (GEVD) is frequently used to fit the block maximum of environmental parameters such as the annual maximum wind speed. There are several methods for estimating the parameters of the GEV distribution, including the least-squares method (LSM). However, the application of the LSM with the expected order statistics has not been reported. This study fills this gap by proposing a fitting method based on the expected order statistics. The study also proposes a plotting position to approximate the expected order statistics; the proposed plotting position depends on the distribution shape parameter. The use of this approximation for distribution fitting is carried out. Simulation analysis results indicate that the developed fitting procedure based on the expected order statistics or its approximation for GEVD is effective for estimating the distribution parameters and quantiles. The values of the probability plotting correlation coefficient that may be used to test the distributional hypothesis are calculated and presented. The developed fitting method is applied to extreme thunderstorm and non-thunderstorm winds for several major cities in Canada. Also, the implication of using the GEVD and Gumbel distribution to model the extreme wind speed on the structural reliability is presented and elaborated.

• 한국수자원학회논문집
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• 제48권1호
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• pp.37-44
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• 2015

본 연구에서는 Grid method를 사용하여 베이지안 비정상성 확률강우량 산정 모형을 확립하였다. 강우 극치자료의 분포로 Gumbel 분포를 채택하였으며, 분포형의 매개변수에 사전분포를 적용하고, 사전분포에 포함된 매개변수에는 초사전 분포를 적용하여 계층적 베이지안 모형을 구성하였다. Grid method는 매개변수의 발생가능 전 구간에 대하여 확률적으로 더 높은 뒷받침이 있는 하위 구간에서 난수를 직접 생성하여 집합을 구성함으로써 잘못된 결과를 도출할 수 가능성이 높은 상황에서도 보다 정확한 매개변수의 추정을 가능케 하므로 매개변수의 추정과정에서 비표준분포로 나타나는 조건부 확률밀도함수를 통한 난수의 추출은 기존에 사용해 온 Metropolis Hastings 알고리즘이 아닌 Grid method를 사용하였다. 개발된 모형은 서울의 1973년부터 2012년까지의 시강우자료를 이용하여 미래에 대한 재현기간에 따른 확률강수량을 산정하였으며, 그 결과로 기존 정상성 가정에 비해 목표연도에 따라 5%에서 8%정도의 증가율을 나타냈다.