• KSCE Journal of Civil and Environmental Engineering Research
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• v.29 no.3A
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• pp.189-197
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• 2009

In this study, truck weight data and load effects of single truck on bridges are analyzed for development of new vehicular load model of the reliability-based bridge design code. Rational load model and statistical properties of loads are important for developing reliability-based design code. In this study, truck weight data collected at four locations are used as well as data from four locations in other studies. Truck weight data are collected from WIM or BWIM system, which are known to give reliable data. Typical truck types, dimensions and axle weight distribution are determined. Probability distributions of upper 20% total truck weight are assumed as Extreme Type I and 100 years maximum truck weights are estimated by linear regression on the probability paper. The load effects of trucks having estimated maximum weights are analyzed for span length from 10 m to 200 m.

• Journal of Mechanical Science and Technology
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• v.17 no.6
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• pp.844-853
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• 2003

In this paper, a dynamic analysis of the reciprocating compression mechanism of a small refrigeration compressor is performed. In the problem formulation of the mechanism dynamics, the viscous frictional force between the piston and the cylinder wall is considered in order to determine the coupled dynamic behaviors of the piston and the crankshaft. Simultaneous solutions are obtained for the equations of motion of the reciprocating mechanism and the time-dependent Reynolds equations for the lubricating film between the piston and the cylinder wall and for the oil films on the journal bearings. The hydrodynamic forces of the journal bearings are calculated by using a finite bearing model along with the Gumbel boundary condition. A Newton-Raphson procedure is employed in solving the nonlinear equations for the piston and crankshaft. The developed computer program can be used to calculate the complete trajectories of the piston and the crankshaft as functions of the crank angle under compressor-running conditions. The results explored the effects of the radial clearance of the piston, oil viscosity, and mass and mass moment of inertia of the piston and connecting rod on the stability of the compression mechanism.

• Computers and Concrete
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• v.25 no.5
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• pp.447-460
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• 2020

This paper deals with the characteristics of reinforcement corrosion in concrete beams under the influence of sustained loads. The evolution and distribution laws of the reinforcement corrosion were measured periodically over time. The results show that sustained load exhibits a pronounced exacerbating effect on the reinforcement corrosion, and enlarges the nonuniformity level of corrosion as the load level increases. Accompanied with the continuous formation of the rust, the corrosion rate was also observed to be highly nonlinear and time-dependent. Moreover, to visually and quantitatively analyze the distribution of reinforcement corrosion, the 3D scanning technology combined with the probability statistics analysis was adopted, and the observed nonuniformity can be well described by the Gumbel distribution. Finally, an approach based on the three-phase spherical model was proposed to estimate the reinforcement corrosion, taking account of the effects of sustained load on the changes of concrete porosity and oxygen diffusivity.

• Communications for Statistical Applications and Methods
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• v.25 no.1
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• pp.15-27
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• 2018

Parametric method of flood frequency analysis involves fitting of a probability distribution to observed flood data. When record length at a given site is relatively shorter and hard to apply the asymptotic theory, an alternative distribution to the generalized extreme value (GEV) distribution is often used. In this study, we consider the beta-P distribution (BPD) as an alternative to the GEV and other well-known distributions for modeling extreme events of small or moderate samples as well as highly skewed or heavy tailed data. The L-moments ratio diagram shows that special cases of the BPD include the generalized logistic, three-parameter log-normal, and GEV distributions. To estimate the parameters in the distribution, the method of moments, L-moments, and maximum likelihood estimation methods are considered. A Monte-Carlo study is then conducted to compare these three estimation methods. Our result suggests that the L-moments estimator works better than the other estimators for this model of small or moderate samples. Two applications to the annual maximum stream flow of Colorado and the rainfall data from cloud seeding experiments in Southern Florida are reported to show the usefulness of the BPD for modeling hydrologic events. In these examples, BPD turns out to work better than $beta-{\kappa}$, Gumbel, and GEV distributions.

• Wind and Structures
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• v.34 no.6
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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.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.368-368
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• 2021

기후 변화로 인한 극한사상의 크기와 빈도 변화를 예측하는 것은 수공 인프라 설계에 있어 주된 관심사 중 하나이다. 보통 극한사상에 대한 강도, 빈도, 지속시간에 대한 정보가 필요하며, 이는 일반적으로 IDF(Intensity-Duration-Frequency) 곡선으로부터 추출된다. 최근 CMIP(Coupled Model Intercomparison Project) 6단계에서 새로운 이산화탄소 배출 시나리오와 업데이트된 기후모델을 이용하여 미래의 기후에 대한 예측 시계열을 발표했으므로, 미래 기후 변화 시나리오를 기반으로 IDF 곡선을 새로 추정하고 미래 기간의 변화를 평가할 필요가 있다. 본 연구에서는 한국의 40개 지역에 대해 일단위 자료를 시단위로 축소(downscaling)한 후, 확률론적 일기생성기(stochastic weather generator)를 이용하여 30년 시단위 시계열을 100개의 앙상블로 생성하였다. 생성된 시계열로부터 연최대강수량 시계열을 재구성하여 GEV 분포와 gumbel 분포에 적용하였다. 적합도 검정(Anderson-Darling(AD) 검정 및 Kolmogorov-Smirnov(KS) 검정)을 수행하였으며, 과거 자료를 기반으로 생성된 IDF 곡선과 비교 검증하였다. CMIP5의 기후변화 자료를 사용한 결과와 CMIP6 기후변화의 결과를 비교하였으며, 본 연구의 주요 결과는 다음과 같다. (1) 향후 강우 강도는 증가할 것이며 강우 강도의 증가는 말기에 현저하게 관찰될 것이다. (2) 시간별 강우 강도의 미래 변화가 일단위 강우 강도보다 더 크다. (3) 강우 강도의 불확실성을 정량화하기 위해 앙상블을 사용해야 한다. (4) 강우 강도의 미래 변화에 대한 공간적인 경향이 확인된다. 시단위 시계열 앙상블을 생성하여 추정된 IDF 곡선에 대한 정보는 기후 변화의 영향을 평가하고 적절한 적응 및 대응 전략을 개발하는 데 도움이 될 것이다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.410-410
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• 2022

기후변화에 관한 정부간 협의체(Intergovernmental Panel on Climate Change, IPCC)에서는 지난해부터 제6차 평가보고서(Sixth Assessment Report, AR6)를 준비하고 있으며, 최근 Working Group II에서 수행한 기후변화 영향, 적응 및 취약성(Impacts, Adaptation and Vulnerability) 보고서를 공개하였다. 보고서는 기존의 Representative Concentration Pathway (RCP) 시나리오에 사회경제적 조건을 추가로 고려한 Shared Socioeconomic Pathway (SSP) 시나리오를 제시하였고, 세계기후연구프로그램(World Climate Research Programme, WCRP)의 Coupled Model Intercomparison Project (CMIP)에서 제공하는 6단계(Phase 6) 미래 전망 자료를 적용하였다. 본 연구에서는 기후변화로 인한 미래 극한 강우량의 통계적 특성을 파악하기 위하여 CMIP6에서 제공하는 General Circulation Models (GCMs) 기반 미래 강우자료를 수집하여 부산광역시를 중심으로 분석하였다. 4개의 SSP (SSP126, SSP245, SSP370, SSP585) 시나리오별로 10개 GCMs의 모의 결과를 사용하였다. Gumbel 분포형과 확률가중모멘트법을 이용하여 미래 극한 강우량을 산정하였고, 현재 모의기간(S0, 1983-2014) 대비 미래 전망기간(S1, 2015-2044; S2, 2041-2070; S3, 2071-2100)의 변화를 재현기간(return period, T)별로 분석하여 제시하였다.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.36 no.5
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• pp.791-803
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• 2016

Recently, frequency of extreme rainfall events in South Korea has been substantially increased due to the enhanced climate variability. Korea is prone to flooding due to being surrounded by mountains, along with high rainfall intensity during a short period. In the past three decades, an increase in the frequency of heavy rainfall events has been observed due to enhanced climate variability and climate change. This study aimed to analyze extreme rainfalls informed by their frequency of occurrences using a long-term rainfall data. In this respect, we developed a Poisson-Generalized Pareto Distribution (Poisson-GPD) based rainfall frequency method which allows us to simultaneously explore changes in the amount and exceedance probability of the extreme rainfall events defined by different thresholds. Additionally, this study utilized a Bayesian approach to better estimate both parameters and their uncertainties. We also investigated the synoptic patterns associated with the extreme events considered in this study. The results showed that the Poisson-GPD based design rainfalls were rather larger than those of based on the Gumbel distribution. It seems that the Poisson-GPD model offers a more reasonable explanation in the context of flood safety issue, by explicitly considering the changes in the frequency. Also, this study confirmed that low and high pressure system in the East China Sea and the central North Pacific, respectively, plays crucial roles in the development of the extreme rainfall in South Korea.

• The Korean Journal of Financial Management
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• v.23 no.1
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• pp.193-225
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• 2006

The purpose of this paper is to analyze contagion in Asian foreign exchange markets using Extreme Value Theory and Copula. Our application deals with asymptotic dependence of daily exchange rate return for a sample of eight countries over period 1997.1.1-2005.4.13. The empirical results are summarized as follows. Firstly, Gumbel Copula is a good model to our data according to the value of AIC. Secondly, the extremal dependence between East Asian crisis countries became lower in the post crisis period than the crisis period. Thirdly, It seemed that high extremal dependence exists between East Asian countries with Singapore. Fourthly, the tail dependence between Indonesia, Malaysia, Thailand, Philippine became higher in the crisis period than the total period and post crisis period. Fifthly, the fact that the extremal dependence between Korea and Indonesia, Malaysia, Thailand, Philippine did not increase during the Asian Financial Crisis showed that the contagion effect was not the reason of the Korea's Fiancial Crisis. Sixthly, the extremal dependence between Asian exchange markets was not very high while comparing with the European exchange markets.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.22 no.3
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• pp.193-200
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• 2022

In this study, the finite-failure NHPP software reliability model was applied to the software development model based on the Weibull lifetime distribution (Goel-Okumoto, Rayleigh, Type-2 Gumbe), which is widely used in the software reliability field, and then the cost attributes were compared and evaluated. For this study, failure time data detected during normal operation of the software system were collected and used, the most-likelihood estimation (MLE) method was applied to the parameter estimation of the proposed model, and the calculation of the nonlinear equation was solved using the binary method. As a result, first, in the software development model, when the cost of testing per unit time and the cost of removing a single defect increased, the cost increased but the release time did not change, and when the cost of repairing failures detected during normal system operation increased, the cost increased and the release time was also delayed. Second, as a result of comprehensive comparative analysis of the proposed models, it was found that the Type-2 Gumble model was the most efficient model because the development cost was lower and the release time point was relatively faster than the Rayleigh model and the Goel-Okumoto basic model. Third, through this study, the development cost properties of the Weibull distribution model were newly evaluated, and the analyzed data is expected to be utilized as design data that enables software developers to explore the attributes of development cost and release time.