• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.4267-4275
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• 2015

Prefabricated houses are fabricated at the factory for approximately 60 to 80% of the entire construction process, and assembled in the field. In the process of transporting and lifting, internal and external finishes of the unit module are concerned about damages. The purpose of this study is to improve the fixing equipment by analyzing load behavior. The improved fixing equipment would minimize the deformation of internal and external finishes. In order to develop the improved fixing equipment, transporting load on the fixing equipment is analyzed using Monte Carlo simulations, and structural performance is verified by the non-linear finite element analysis. Statistical analysis shows load distribution of unit module is similar with extreme value distribution. Based on the statistical analysis and Monte Carlo simulation, the maximum transporting load is 28.9kN and 95% confidence interval of transporting load is -1.22kN to 9.5kN. The nonlinear structural analysis shows improved fixing equipment is not destructed to the limit load of 35.3kN and withstands the load-bearing in the 95% confidence interval of transporting load.

• Journal of Korea Water Resources Association
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• v.49 no.4
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• pp.335-346
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• 2016

This study produced the parameter maps of the Modified Bartlett-Lewis Rectangular Pulse (MBLRP) stochastic rainfall generation model across South Korea and developed and validated the web application that automates the process of rainfall generation based on the produced parameter maps. To achieve this purpose, three deferent sets of parameters of the MBLRP model were estimated at 62 ground gage locations in South Korea depending on the distinct purpose of the synthetic rainfall time series to be used in hydrologic modeling (i.e. flood modeling, runoff modeling, and general purpose). The estimated parameters were spatially interpolated using the Ordinary Kriging method to produce the parameter maps across South Korea. Then, a web application has been developed to automate the process of synthetic rainfall generation based on the parameter maps. For validation, the synthetic rainfall time series has been created using the web application and then various rainfall statistics including mean, variance, autocorrelation, probability of zero rainfall, extreme rainfall, extreme flood, and runoff depth were calculated, then these values were compared to the ones based on the observed rainfall time series. The mean, variance, autocorrelation, and probability of zero rainfall of the synthetic rainfall were similar to the ones of the observed rainfall while the extreme rainfall and extreme flood value were smaller than the ones derived from the observed rainfall by the degree of 16%-40%. Lastly, the web application developed in this study automates the entire process of synthetic rainfall generation, so we expect the application to be used in a variety of hydrologic analysis needing rainfall data.

• Wind and Structures
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• v.38 no.4
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• pp.309-323
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• 2024

The gust factor and turbulence intensity are two crucial parameters that characterize the properties of turbulence. In tropical cyclones (TCs), these parameters exhibit significant variability, yet there is a lack of established formulas to account for their probabilistic characteristics with consideration of their inherent connection. On this condition, a probabilistic analysis of gust factors and turbulence intensities of TCs is conducted based on fourteen sets of wind data collected at the Sutong Cable-stayed Bridge site. Initially, the turbulence intensities and gust factors of recorded data are computed, followed by an analysis of their probability densities across different ranges categorized by mean wind speed. The Gaussian, lognormal, and generalized extreme value (GEV) distributions are employed to fit the measured probability densities, with subsequent evaluation of their effectiveness. The Gumbel distribution, which is a specific instance of the GEV distribution, has been identified as an optimal choice for probabilistic characterizations of turbulence intensity and gust factor in TCs. The corresponding empirical models are then established through curve fitting. By utilizing the Gumbel distribution as a template, the nexus between the probability density functions of turbulence intensity and gust factor is built, leading to the development of a generalized probabilistic model that statistically describe turbulence intensity and gust factor in TCs. Finally, these empirical models are validated using measured data and compared with suggestions recommended by specifications.

• Proceedings of the Korean Society of Agricultural Engineers Conference
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• 1998.10a
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• pp.318-324
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• 1998

This study was conducted to derive optimal design floods by Generalized Extreme-value(GEV) distribution for the annual maximum series at ten watersheds along Han, Nagdong, Geum, Yeongsan and Seomjin river systems. Adequacy for the analysis of flood data used in this study was established by the tests of Independence, Homogeneity, detection of Outliers. L-coefficient of variation, L-skewness and L-kurtosis were calculated by L-moment ratio respectively. Parameters were estimated by the Methods of Moments and L-Moments. Design floods obtained by Methods of Moments and L-Moments using different methods for plotting positions in GEV distribution were compared by the relative mean and relative absolute error. It was found that design floods derived by the method of L-moments using weibull plotting position formula in GEV distribution are much closer to those of the observed data in comparison with those obtained by method of moments using different formulas for plotting positions in view of relative mean and relative absolute error.

• Journal of Industrial Technology
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• v.33 no.A
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• pp.41-48
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• 2013

A statistical downscaling methodology has been developed to investigate future daily wind speeds over South Korea. This methodology includes calibration of the statistical downscaling model by using large-scale atmospheric variables encompassing NCEP/NCAR reanalysis data, validation of the model for the calibration period, and estimation of the future wind speed based on the general circulation model (GCM) outputs of scenario A1B of the CGCM3. Based on the scenario A1B of the CGCM3 model, the potential impacts of climate change on the daily surface wind speed is relatively small (+/- 1m/s) in South Korea.

• Magazine of the Korean Society of Agricultural Engineers
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• v.44 no.6
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• pp.49-60
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• 2002

This study was conducted to estimate the design flood by the determination of best fitting order of LH-moments of the annual maximum series at six and nine watersheds in Korea and Australia, respectively. Adequacy for flood flow data was confirmed by the tests of independence, homogeneity, and outliers. Gumbel (GUM), Generalized Extreme Value (GEV), Generalized Pareto (GPA), and Generalized Logistic (GLO) distributions were applied to get the best fitting frequency distribution for flood flow data. Theoretical bases of L, L1, L2, L3 and L4-moments were derived to estimate the parameters of 4 distributions. L, L1, L2, L3 and L4-moment ratio diagrams (LH-moments ratio diagram) were developed in this study. GEV distribution for the flood flow data of the applied watersheds was confirmed as the best one among others by the LH-moments ratio diagram and Kolmogorov-Smirnov test. Best fitting order of LH-moments will be derived by the confidence analysis of estimated design flood in the second report of this study.

• Proceedings of the Earthquake Engineering Society of Korea Conference
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• 1997.10a
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• pp.41-48
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• 1997

The seismic risk in Seoul Metropolitan Area(latitude 37.0$^{\circ}$~37.8$^{\circ}$, longitude 126.5$^{\circ}$~127.5$^{\circ}$)based on all Korean earthquake data of Modified Mercalli Intensity equal to or greater than V is evaluated by extreme value method and point source method. The seismic risk estimated from all data turned out to be lower than from the data since the Chosen dynasty during which seismic data appear to be rather complete. The damaging earthquake of park horizontal ground acceleration grater than 0.1g turns out to occur with 90% probability of being exceeded in 200 years when the data since the Chosen Dynasty are used.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 1990.04a
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• pp.31-36
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• 1990

The probabilistic characteristics of wind loads have been analyzed using statistical data on wind speeds, pressure coefficient, exposure coefficient, and gust factor. The wind speed data collected in 25 nationwide weather stations have been modified to be consistent in measuring height, exposure condition as well as averaging time, Having performed Monte Carlo simulation for various heights and site conditions, the statistical models of wind loads were determined, in which Type-I extreme value distribution has been applied. The models also incorporate a reduction factor of 0.85 to account for the reduced probability that the maximum wind speed will occur in a direction most unfavorable to the response of structure.

• Journal of the Architectural Institute of Korea Structure & Construction
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• v.35 no.10
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• pp.191-198
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• 2019

In this paper the evaluation scheme for determining torsional irregularity of Hanok has been proposed. The proposed method can evaluate torsional irregularity of Hanok easily only with characteristics of Hanok shapes, arrangement of lateral load resisting frames and their lateral stiffness without time consuming and complicate 3-dimensional structural analysis. The proposed formula is expressed as allowable maximum eccentricity, and torsional irregularity is evaluated by comparing this value with actual eccentricity. The applicability of the proposed scheme was evaluated by applying it to the line shape plan Hanok with two symmetrically arranged walls and the result was expressed by formula and graph. The results showed that the allowable maximum eccentricity is 10% of plan dimension perpendicular to the seismic load when the walls are placed at the extreme end. The proposed formula was expressed as a generalized formula so it can be applied generally to the various plan shape and wall arrangement of Hanok.

• Wind and Structures
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• v.31 no.6
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• pp.549-560
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• 2020

Methods for stochastic simulation of non-Gaussian wind pressure have increasingly addressed the efficiency and accuracy contents to offer an accurate description of the extreme value estimation of the long-span and high-rise structures. This paper presents a linear prediction and z-transform (LPZ) based Cumulative distribution function (CDF) mapping algorithm for the simulation of multivariate non-Gaussian fluctuating wind pressure. The new algorithm generates realizations of non-Gaussian with prescribed marginal probability distribution function (PDF) and prescribed spectral density function (PSD). The inverse linear prediction and z-transform function (ILPZ) is deduced. LPZ is improved and applied to non-Gaussian wind pressure simulation for the first time. The new algorithm is demonstrated to be efficient, flexible, and more accurate in comparison with the FFT-based method and Hermite polynomial model method in two examples for transverse softening and longitudinal hardening non-Gaussian wind pressures.