• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.246-246
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• 2015

Runoff at any given location along a stream can be expressed as a function of its upstream area. The runoff-drainage area relationship can be well expressed as power-law (Brush, 1961) with its exponent, ranging as high as unity (e.g., Stall and Fok, 1968) and as low as 0.5 in natural rivers. Here, we study the runoff-drainage area relationships for Han River and Nakdong River, Korea. We find that the relationships follow power-law and their exponents are highly related with occurrence frequency of flow. To support this, we analyze flow frequency with historical data measured over decades. Findings in this study can broaden our understanding on mechanisms behind the catchment response to runoff.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2020년도 학술발표회
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• pp.121-121
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• 2020

Varying dominant processes, including Tropical Cyclone (TC) and non-TC rainfall events, have been known to drive the occurrence of precipitation in South Korea. With the changes in the pattern of the Earth's climate due to anthropogenic activities, nonstationarity or changes in the magnitude and frequency of these dominant processes have been separately observed for the past decades and are expected to continue in the coming years. These changes often cause unprecedented hydrologic events such as extreme flooding which pose a greater risk to the society. This study aims to take into account a more reliable future climate condition with two dominant processes. Diverse statistical models including the hidden markov chain, K-nearest neighbor algorithm, and quantile mappings are utilized to mimic future rainfall events based on the recorded historical data with the consideration of the varying effects of TC and non-TC events. The data generated is then utilized to the hydrologic model to conduct a flood frequency analysis. Results in this study emphasize the need to consider the nonstationarity of design rainfalls to fully grasp the degree of future flooding events when designing urban water infrastructures.

• 한국지진공학회:학술대회논문집
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• 한국지진공학회 1998년도 춘계 학술발표회 논문집 Proceedings of EESK Conference-Spring 1998
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• pp.52-57
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• 1998

Becaruse of the continual occurrence of minor and moderate earthquake in Korean peninsula, it is generally considered that Korean is nor located in safe region against probable earthquake and more, even though being recognized as a safe contry in earthquake. It is in particular noted that nowadays there has been much concern about undesirable disaster due to unexpected earthquake since the disaster of 1995 Kobe earthquake. Thus, the objective of this research is to develop appropriate design spectrum which could be practicably used in seismic design of important structures taking into consideration of local physical characteristics. Particularly, we have to keep in mind the lessons from 1985 Mexico earthquake which had disregarded deep research on local ground conditions, being a possible magnification phenomena of ground motions in weak soil layer. Various spectra has been described based on the analysis of historical earthquakes, and appropriate design spectrum has been proposed herein.

• 물과 미래
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• 제28권5호
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• pp.191-203
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• 1995

본 연구에서는 한강의 주요 수위관측지점중 하나인 팔당댐 하류 고안지점의 과거 연최대 홍수위자료를 1994년 단면을 기준으로 홍수위를 환산하고 홍수 빈도해석을 통하여 확률홍수량을 산정하였다. 과거 홍수위자료에 대한 현 하상상태에서의 환산수위를 구하기 위해서 최근에 새롭게 확립된 수위-유량 관계곡선을 이용하였다. 기왕의 연최대 홍수량자료를 기본자료로 하여 수문해석에서 많이 이용되고 있는 10개의 확률분포형을 가지고, 확률가중 모멘트법에 의해 매개변수를 추정하고, 적합도 검정을 한 결과 gamma-2, gamma-3 분포형이 최적분포형인 것으로 나타났으며, 빈도해석을 통해 재현기간별로 확률홍수량 및 확률홍수위를 산정하였다. 또한, 결측된 자료를 보완하기 위하여 과거 홍수정보를 이용하는 기법을 사용하여 기왕의 홍수량에 대한 빈도해석을 실시하여 확률분포형에 의한 산정값과 비교하였다.

• 대한조선학회논문집
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• 제55권2호
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• pp.93-102
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• 2018

Quantitative Risk Assessment (QRA) has been used in shipping and offshore industries for many years, supporting the decision-making process to guarantee safe running at different stages of design, fabrication and throughout service life. The assessments of a risk perspective are informed by the frequency of events (probability) and the associated consequences. As the number of offshore platforms increases, so does the length of subsea pipelines, thus there is a need to extend this approach and enable the subsea industry to place more emphasis on uncertainties. On-board operations can lead to objects being dropped on subsea pipelines, which can cause leaks and other pipeline damage. This study explains how to conduct hit frequency analyses of subsea pipelines, using historical data, and how to obtain a finite number of scenarios for the consequences analysis. An example study using probabilistic methods is used.

• 한국농공학회지
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• 제22권3호
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• pp.75-87
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• 1980

Most hydro]ogic phenomena are the complex and organic products of multiple causations like climatic and hydro-geological factors. A certain significant correlation on the run-off in river basin would be expected and foreseen in advance, and the effect of each these causual and associated factors (independant variables; present-month rainfall, previous-month run-off, evapotranspiration and relative humidity etc.) upon present-month run-off(dependent variable) may be determined by multiple regression analysis. Functions between independant and dependant variables should be treated repeatedly until satisfactory and optimal combination of independant variables can be obtained. Reliability of the estimated function should be tested according to the result of statistical criterion such as analysis of variance, coefficient of determination and significance-test of regression coefficients before first estimated multiple regression model in historical sequence is determined. But some error between observed and estimated run-off is still there. The error arises because the model used is an inadequate description of the system and because the data constituting the record represent only a sample from a population of monthly discharge observation, so that estimates of model parameter will be subject to sampling errors. Since this error which is a deviation from multiple regression plane cannot be explained by first estimated multiple regression equation, it can be considered as a random error governed by law of chance in nature. This unexplained variance by multiple regression equation can be solved by stochastic approach, that is, random error can be stochastically simulated by multiplying random normal variate to standard error of estimate. Finally hybrid model on estimation of monthly run-off in nonhistorical sequence can be determined by combining the determistic component of multiple regression equation and the stochastic component of random errors. Monthly run-off in Naju station in Yong-San river basin is estimated by multiple regression model and hybrid model. And some comparisons between observed and estimated run-off and between multiple regression model and already-existing estimation methods such as Gajiyama formula, tank model and Thomas-Fiering model are done. The results are as follows. (1) The optimal function to estimate monthly run-off in historical sequence is multiple linear regression equation in overall-month unit, that is; Qn=0.788Pn+0.130Qn-1-0.273En-0.1 About 85% of total variance of monthly runoff can be explained by multiple linear regression equation and its coefficient of determination (R2) is 0.843. This means we can estimate monthly runoff in historical sequence highly significantly with short data of observation by above mentioned equation. (2) The optimal function to estimate monthly runoff in nonhistorical sequence is hybrid model combined with multiple linear regression equation in overall-month unit and stochastic component, that is; Qn=0. 788Pn+0. l30Qn-1-0. 273En-0. 10+Sy.t The rest 15% of unexplained variance of monthly runoff can be explained by addition of stochastic process and a bit more reliable results of statistical characteristics of monthly runoff in non-historical sequence are derived. This estimated monthly runoff in non-historical sequence shows up the extraordinary value (maximum, minimum value) which is not appeared in the observed runoff as a random component. (3) "Frequency best fit coefficient" (R2f) of multiple linear regression equation is 0.847 which is the same value as Gaijyama's one. This implies that multiple linear regression equation and Gajiyama formula are theoretically rather reasonable functions.

• Wind and Structures
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• 제18권4호
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• pp.347-373
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• 2014

Since its development in the early 1980's the force balance technique has become a standard method in the efficient determination of structural loads and responses. Its usefulness lies in the simplicity of the physical model, the relatively short records required from the wind tunnel testing and its versatility in the use of the data for different sets of dynamic properties. Its major advantage has been the ability to provide results in a timely manner, assisting the structural engineer to fine-tune their building at an early stage of the structural development. The analysis of the wind tunnel data has evolved from the simple un-coupled system to sophisticated methods that include the correction for non-linear mode shapes, the handling of complex geometry and the handling of simultaneous measurements on multiple force balances for a building group. This paper will review some of the components in the force balance data analysis both in historical perspective and in its current advancement. The basic formulation of the force balance methodology in both frequency and time domains will be presented. This includes all coupling effects and allows the determination of the resultant quantities such as resultant accelerations, as well as various load effects that generally were not considered in earlier force balance analyses. Using a building model test carried out in the wind tunnel as an example case study, the effects of various simplifications and omissions are discussed.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2018년도 학술발표회
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• pp.158-158
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• 2018

Drought is a recurrent natural hazard in Bangladesh. It has significant impacts on agriculture, environment, and society. Well-timed information on the onset, extent, intensity, duration, and impacts of drought can mitigate the potential drought-related losses. Thus, drought characteristics need to be explained in terms of frequency, severity, and duration. This paper aims to characterize the spatial and temporal pattern of meteorological drought using EDI and illustrated drought severity over Bangladesh. Twenty-seven (27) station-based daily rainfall data for the study period of 1981-2015 were used to calculate the EDI values over Bangladesh. The evaluation of EDI is conducted for 4 sub-regions over the country to confirm the historical drought record-developed at the regional scale. The finding shows that on average, the frequency of severe to extreme drought is approximately 0.7 events per year. As a result of the regional analysis, most of the recorded historical drought events were successfully detected during the study period. Additionally, the seasonal analysis showed that the extreme droughts were frequently hit in northwestern, middle portion of the eastern and small portion of central parts of Bangladesh during the Kharif(wet) and Rabi(dry) seasons. The severe drought was affected recurrently in the central and northern regions of the country during all cropping seasons. The study also points out that the northern, south-western and central regions in Bangladesh are comparatively vulnerable to both extreme and severe drought event. The study showed that EDI would be a useful tool to identify the drought-prone area and time and potentially applicable to the climate change-induced drought evolution monitoring at regional to the national level in Bangladesh. The outcome of the present study can be used in taking anticipatory strategies to mitigate the drought damages on agricultural production as well as human sufferings in drought-prone areas of Bangladesh.

• Smart Structures and Systems
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• 제31권5호
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• pp.485-500
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• 2023

Machine learning-based structural health monitoring (ML-based SHM) methods are researched extensively in the recent decade due to the availability of advanced information and sensing technology. ML methods are well-known for their pattern recognition capability for complex problems. However, the main obstacle of ML-based SHM is that it often requires pre-collected historical data for model training. In most actual scenarios, damage presence can be detected using the unsupervised learning method through anomaly detection, but to further identify the damage types would require prior knowledge or historical events as references. This creates the cold-start problem, especially for new and unobserved structures. Modal-based methods identify damages based on the changes in the structural global properties but often require dense measurements for accurate results. Therefore, a two-stage hybrid modal-machine learning damage detection scheme is proposed. The first stage detects damage presence using Principal Component Analysis-Frequency Response Function (PCA-FRF) in an unsupervised manner, whereas the second stage further identifies the damage. To solve the cold-start problem, mode shape assessment using the first mode is initiated when no trained model is available yet in the second stage. The damage identified by the modal-based method would be stored for future training. This work highlights the performance of the scheme in alleviating the cold-start issue as it transitions through different phases, starting from zero damage sample available. Results showed that single and multiple damages can be identified at an acceptable accuracy level even when training samples are limited.

• 농촌계획
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• 제9권2호
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• pp.29-37
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• 2003

The objectives of this study are to develop an agricultural drought evaluation model based on administrative boundaries and to assist the effective drought-related decision-making of local governments. The model which was named ADEM(Administrative Drought Evaluation Model for Paddies) is designed to simulate daily water balance between available water quantities from various agricultural water facilities such as reservoirs, wells, pump stations, etc. and water requirements in paddies. And in order to numerically describe the agricultural drought severity, two indices were defined; One is ADFP(Agricultural Drought Frequency for Paddies) which is calculated with a frequency analysis of monthly water deficit, and the other is ADIP(Agricultural Drought Index for Paddies) with a scale of $-4.2{\sim}+4.2$. The developed model was applied to Yeoju district and showed good correspondence with the historical records of drought.