• Proceedings of the Korea Water Resources Association Conference
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• 2017.05a
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• pp.150-150
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• 2017

기후변화로 인하여 극한 홍수와 극한 가뭄 발생이 증가할 것으로 전망하고 있어 이에 대한 위험이 대두되고 있는 실정이다. 홍수 및 가뭄 수문시계열의 빈도해석시에 일반적으로 활용되는 정상성 빈도해석기법은 수문자료의 정상성을 기반으로 한 빈도해석이 대부분이기 때문에 기후변화 및 수문자료의 비정상성을 반영한 새로운 빈도해석 기법이 요구되고 있는 상황이다. 본 연구에서는 5개의 대표 관측지점(서울, 포항, 추풍령, 여수, 광주)를 선별하고 1976년부터 2015년까지 일강우자료를 활용하여 기상학적 가뭄지수인 SPI(Standardized Precipitation Index)를 산정하였다. 산정한 SPI의 경향성을 Mann-Kendall 분석을 하였으며, 정상성 및 비정상성 빈도해석을 위하여 최적확률분포로 선정된 GEV 분포 적용하였다. 본 연구에서는 가뭄빈도해석을 위하여 SPI를 입력자료로 활용하였으며, 산정된 SPI의 비정상성을 반영한 비정상성 빈도해석의 경우 Bayesian 모형을 기반으로 한 MCMC(Markov Chain Monte Carlo) 모의를 이용하여 극치분포의 사후분포 매개변수를 추정하였다. 추정 값을 바탕으로 하여 가뭄의 관측소별 빈도해석을 실시하였고 재현기간별-지속기간별 가뭄심도를 추정하여 관측소별 가뭄심도-지속기간-빈도(SDF,Severity-Duration-Frequency) 곡선을 유도하였다. 본 연구를 통하여 정상성과 비정상성 빈도해석 결과의 비교연구를 수행하였으며 기후변화에 따른 비정상 시계열로 구성된 가뭄빈도해석에 매우 유용하게 적용될 수 있을 것으로 나타났다.

• Proceedings of the Korea Water Resources Association Conference
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• 2018.05a
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• pp.312-312
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• 2018

우리나라의 기후 지형적 특성에 따라 연강수량의 50% 이상이 여름철에 내리며 이러한 짧은 기간에 집중적으로 내리는 강수패턴 조건하에서 수공구조물 설계시 대부분 극치빈도분석을 활용한다. 우리나라의 경우 단일 Gumbel 분포를 활용한 극치빈도분석을 많이 이용한다. 하지만, 최근 이상기후로 인하여 전세계적으로 강수패턴의 특징이 급격히 변하고 있으며, 우리나라의 강수패턴 또한 바뀌어가고 있다. 연강수량의 대부분은 태풍과 장마로 인한 강수량으로 이루어져 있고, 일반적으로 두 개의 모집단으로 이루어진 형태를 보인다. 앞선 연구에서 두 개 이상의 첨두를 가지는 형태의 연최대강수량 자료에 대해 8개의 지속시간별(1, 2, 3, 6, 9, 12, 18, 24hr)로 Bayesian 기법의 단일 Gumbel 분포형과 혼합 Gumbel분포형 기반의 극치빈도분석 결과를 비교하였고, 혼합 Gumbel 분포형이 이중첨두 부분의 거동을 효과적으로 모의하는 것을 확인하였다. 본 연구에서는 이상기후로 인한 강수량의 특징의 급격한 변화에 일정한 패턴이 있음을 가정하고 이중첨두의 연 최대일강수량 자료에 대해 혼합 Gumbel 분포형 기반 비정상성 빈도분석을 실시하였다. 정상성 빈도분석과의 비교를 위해 확률분포의 매개변수 산정시 우도함수를 Bayesian 기법을 통해 산정하여 각 분포형의 Bayesian information criterion(BIC) 값을 비교하였다. 비정상성일 경우의 BIC 값이 정상성일 경우 보다 작게 산정되었고, 강수패턴이 경향성을 가지는 것으로 판단할 수 있었다. 비정상성 혼합 Gumbel 분포형 모델은 최근 급격한 강수패턴의 변화에 대한 대응책으로서 활용성이 높을 것으로 기대된다.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.21 no.9
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• pp.1198-1206
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• 1997

The flow characteristics of an intermittent fuel injection into a stationary ambient air were investigated using gasoline. The measurements were made by two-channel, air cooling type Phase Doppler Anemometer(PDA) system (DANTEC, 750 MW). And a pintle type injector of MPI (Multi-point Port Injection) system was utilized as a fuel injector. The PDA receiver optic was set up in a 60.deg. C forward scatter arrangement to obtain the optimum scattering signal of fuel droplets. The data were obtained by synchronizing PDA system with the fuel injection period, and the axial and radial velocity and turbulent components of fuel droplets were mainly measured for the analysis of temporal and spatial distribution depending upon the fuel injection pressures.

• Journal of the Korean Society of Hazard Mitigation
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• v.7 no.5
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• pp.167-178
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• 2007

Based on the kinematic wave equations, the influence of moving rainstorms on the surface runoff were analyzed with a focus on the rainfall distribution types. Applied hypothetical rainfall distribution types of moving rainstorms used are uniform, advanced, delayed and intermediate type. The moving rainstorm velocities applied in this study were $0.125{\sim}2.0m/s$ of moving upstream and downstream direction of plane surface. Simulations were undertaken by varying the rainfall distribution type, moving rainstorm velocity and moving direction, and the results were compared with that of stationary rainfall. The results indicate significant differences in peak discharges and hydrograph shapes for moving rainstorms of various rainfall patterns and moving directions. It shows that the moving rainstorms of downstream direction generate the largest peak runoff at all rainfall distributions. The sensitivity of runoff to rainfall distribution types decreases as storm velocity increases. It is clear that faster rainstorm velocity generates faster peak time and becomes thin hydrographs rapidly.

• Journal of the Institute of Electronics Engineers of Korea SP
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• v.42 no.6
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• pp.195-202
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• 2005

An adaptive segmentation algorithm is used to efficiently target decisions in local non-stationary images. Until now, several adaptive approaches have been proposed as a method of segmentation. However, they can't be directly used for radar target detection because a radar signal has different characteristics from general images. Generally, a histogram of radar signal shows that targets have a relatively small number of frequency functions compared to the background and distribution of background, which have several shapes as the environment changes. In this paper, we propose an adaptive segmentation algorithm using a histogram chord which is a right-down line from maximum pick of frequency function. The proposed method provides thresholds which are optimum for several radar environments because the used chord for threshold search is not significantly effected by interference conditions. Simulation results show that the proposed method is superior to the traditional algorithms, global threshold method and distribution median method, with respect to detection performance.

• Journal of Korea Foresty Energy
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• v.21 no.2
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• pp.17-24
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• 2002

Activated carbons were prepared from pine bark by steam activation, and pore structures and specific surface areas were then investigated. Three different types of kilns were used for the activation. When the stationary-vertical-or stationary-horizontal-type kiln was used for the steam activation to prepare an activated carbon from the bark, it was not possible to produce activated carbon having high specific surface areas exceeding 1,000 $m^2／g$. Using bark powder improved the specific surface area, but it was still not high enough. When the rotary-horizontal-type kiln was used for the activation, the activated carbons prepared had high specific surface areas of more than 1,000$m^2／g$, which was similar to a commercial first-grade activated carbon. The activated carbon prepared by the rotary kiln had a wide distribution of pore size ranging from microporous to mesoporous.

• Journal of Korean Society on Water Environment
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• v.33 no.3
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• pp.256-272
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• 2017

Extreme rainfall has become more frequent over the Korean peninsula in recent years, causing serious damages. In a changing climate, traditional approaches based on historical records of rainfall and on the stationary assumption can be inadequate and lead to overestimate (or underestimate) the design rainfalls. A main objective of this study is to develop a stochastic disaggregation method of seasonal rainfall to hourly extreme rainfall, and offer a way to derive the nonstationary IDF curves. In this study, we propose a novel approach based on a Four-Parameter Beta (4P-beta) distribution to estimate the nonstationary IDF curves conditioned on the observed (or simulated) seasonal rainfall, which becomes the time-varying upper bound of the 4P beta distribution. Moreover, this study employed a Bayesian framework that provides a better way to take into account the uncertainty in the model parameters. The proposed model showed a comparable design rainfall to that of GEV distribution under the stationary assumption. As a nonstationary rainfall frequency model, the proposed model can effectively translate the seasonal variation into the sub-daily extreme rainfall.

• Journal of Korean Society of Coastal and Ocean Engineers
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• v.5 no.3
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• pp.182-190
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• 1993

A numerical technique is presented to calculate the motions of 6 d.o.f and mooring tensions for a catenary moored floating breakwater. The breakwater may be subjected to the 3-D combination of regular or irregular waves and stationary forces. The added mass coefficients at the infinitive frequency of input wave and the variations of damping and exciting force coefficients are calculated using the source distribution method. The coefficients are used to constitute motion equations in time domain which are solved by WiIson-$\theta$ method. The solutions agree quite well with either static displacement determined from Newton method under the stationary force only or 6 d.o.f determined from the frequency domain analysis under regular wave only. An example analysis is also done for a floating breakwater to demonstrate its applicability.

• Journal of Korea Water Resources Association
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• v.46 no.8
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• pp.833-842
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• 2013

The quantile mapping is utilized to reproduce reliable GCM(Global Climate Model) data by correct systematic biases included in the original data set. This scheme, in general, projects the Cumulative Distribution Function (CDF) of the underlying data set into the target CDF assuming that parameters of target distribution function is stationary. Therefore, the application of stationary quantile mapping for nonstationary long-term time series data of future precipitation scenario computed by GCM can show biased projection. In this research the Nonstationary Quantile Mapping (NSQM) scheme was suggested for bias correction of nonstationary long-term time series data. The proposed scheme uses the statistical parameters with nonstationary long-term trends. The Gamma distribution was assumed for the object and target probability distribution. As the climate change scenario, the 20C3M(baseline scenario) and SRES A2 scenario (projection scenario) of CGCM3.1/T63 model from CCCma (Canadian Centre for Climate modeling and analysis) were utilized. The precipitation data were collected from 10 rain gauge stations in the Han-river basin. In order to consider seasonal characteristics, the study was performed separately for the flood (June~October) and nonflood (November~May) seasons. The periods for baseline and projection scenario were set as 1973~2000 and 2011~2100, respectively. This study evaluated the performance of NSQM by experimenting various ways of setting parameters of target distribution. The projection scenarios were shown for 3 different periods of FF scenario (Foreseeable Future Scenario, 2011~2040 yr), MF scenario (Mid-term Future Scenario, 2041~2070 yr), LF scenario (Long-term Future Scenario, 2071~2100 yr). The trend test for the annual precipitation projection using NSQM shows 330.1 mm (25.2%), 564.5 mm (43.1%), and 634.3 mm (48.5%) increase for FF, MF, and LF scenarios, respectively. The application of stationary scheme shows overestimated projection for FF scenario and underestimated projection for LF scenario. This problem could be improved by applying nonstationary quantile mapping.

• Journal of Korea Water Resources Association
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• v.48 no.1
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• pp.37-44
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• 2015

A Bayesian nonstationary probability rainfall estimation model using the Grid method is developed. A hierarchical Bayesian framework is consisted with prior and hyper-prior distributions associated with parameters of the Gumbel distribution which is selected for rainfall extreme data. In this study, the Grid method is adopted instead of the Matropolis Hastings algorithm for random number generation since it has advantage that it can provide a thorough sampling of parameter space. This method is good for situations where the best-fit parameter values are not easily inferred a priori, and where there is a high probability of false minima. The developed model was applied to estimated target year probability rainfall using hourly rainfall data of Seoul station from 1973 to 2012. Results demonstrated that the target year estimate using nonstationary assumption is about 5~8% larger than the estimate using stationary assumption.