• Proceedings of the Korea Water Resources Association Conference
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• 2015.05a
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• pp.99-99
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• 2015

본 연구에서는 금강 유역을 대상으로 토양저류함수모형기반의 개념적 강우유출모형의 장기 유출모의를 평가하였다. 연구유역인 금강 22개 계측유역을 주요 유역특성인자(면적, 경사도, SCS-CN등)을 수문학적 거리 산정방법을 활용하여 3개의 유역그룹을 선정하였다. 적용모형인 개념적 강우유출모형은 3개의 토양저류함수모형[확률분포모형(PDM: Probability Distributed Moisture), 유역습윤지수모형(CWI: Catchment Wetness Index), 수정펜맨타입모형(MP: Modified Penman type model)]과 3개의 유역추적모형[병렬2선형 저류지 유출 모형(2PAR: 2-conceptual reservoirs in parallel), 빠른 지표하 흐름을 고려한 병렬 2선형 저류지 유출모형(2PMP: 2Macro-pre Approach parallel structure), 병렬 3선형 저류지 유출모형(3PAR: 3-conceptual reservoirs in parallel)]의 조합인 9개의 모형을 사용하였으며, 2006년부터 2012년의 일자료를 바탕으로 검정(Calibration), 2001년부터 2005년의 일자료를 검증(Validation)을 Monte carlo method(Uniform Random Sampling)로 수행 후, 모형의 성능은 NSE(Nash sutcliffe Efficiency)로 평가하였다. 분석결과 유역그룹에 대한 모형성능의 편차는 작아서 유역그룹에 대한 토양저류 함수모형의 뚜렷한 상관성을 확인할 수 없었다. 이는 금강 유역을 단일 유역 그룹으로 적용할 수 있음을 제시하고 있다. 검정 검증성능 및 검정매개변수의 개수를 바탕으로 적용성 평가를 실시한 결과에서 토양저류함수모형인 확률분포모형(PDM)과 유역추적모형의 병렬2선형 저류지 유출모형(2PAR)와 빠른 지표하 흐름을 고려한 병렬2선형 저류지 유출모형(2PMP)의 조합이 금강 22개 유역에서 적용성이 우수함을 확인하였다. 향후 이 모형을 바탕으로 금강유역의 대표적인 강우유출모형을 개발하고자 한다.

• Proceedings of the KOR-KST Conference
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• 1997.12b
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• pp.35-72
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• 1997

This study was conducted to develop a methodology to predict utility pole accident rates and to evaluate cost-effectiveness for safety improvement for utility pole accidents. The utility pole accident rate prediction model was based on the encroachment rate approach introduced in the Transportation Research Board special Report 214. The utility pole accident rate on a section of highway depends on the roadside encroachment rate and the lateral extent of encroachment. The encroachment rate is influenced by the horizontal and vertical alignment of the highway as well as traffic volume and mean speed. The lateral extent of encroachment is affected by the horizontal and vertical alignment, the mean speed and the roadside slope. An analytical method to generate the probability distribution function for the lateral extent of encroachment was developed for six kinds of encroachment types by the horizontal alignment and encroachment direction. The encroachment rate was calibrated with the information on highway and roadside conditions and the utility pole accident records collected on the sections of 55mph speed limit of the State Trunk Highway 12 in Wisconsin. The encroachment rate on tangent segment was calibrated as a function of traffic volume with the actual average utility pole accident rates by traffic volume strategies. The adjustment factors for horizontal and vertical alignment were when derived by comparing the actual average utility pole accident rates to the estimations from the model calibrated for tangent and level sections. A computerized benefit-cost analysis procedure was then developed as a means of evaluating alternative countermeasures. The program calculates the benefit-cost ratio and the percent of reduction of utility pole accidents resulting from the implementation of a safety improvement. This program can be used to develop safety improvement alternatives for utility pole accidents when a predetermined performance level is specified.

• Journal of Advanced Navigation Technology
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• v.23 no.2
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• pp.186-193
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• 2019

This paper presents and implements a simple programmable PCM encoder structure uisng the commutation method. In the telemetry system, information is required to assign each data to the channel in order to generate a frame format the data acpuired from the sensor. In this case, when the number of state information is large or the data type is various, there is a necessity to input a large amount of information to each channel. However, the more the number of channels and data, the more probability the error will occur. Therefore, in this paper, the channel information is created using the program. And PCM encoder was implemented to store channel information in ROM. The proposed PCM encoder architecture reduces the likelihood of errors. And it can improve the development speed. The validity of proposed structure is proved by simulation.

• Journal of Korean Society on Water Environment
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• v.27 no.5
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• pp.634-645
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• 2011

A newly developed rainwater harvesting (RWH) system reliability model is evaluated for roof area of buildings in Haeundae District of Busan. RWH system is used to supply water for toilet flushing, back garden irrigation, and air cooling. This model is portable because it is based on a non-parametric precipitation generation algorithm using a markov chain. Precipitation occurrence is simulated using transition probabilities derived for each day of the year based on the historical probability of wet and dry day state changes. Precipitation amounts are selected from a matrix of historical values within a moving 30 day window that is centered on the target day. Then, the reliability of RWH system is determined for catchment area and tank volume ranges using synthetic precipitation data. As a result, the synthetic rainfall data well reproduced the characteristics of precipitation in Busan. Also the reliabilities of RWH system for each of demands were computed to high values. Furthermore, for study area using the RWH system, reduction efficiencies for rooftop runoff inputs to the sewer system and potable water demand are evaluated for 23%, 53%, respectively.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1293-1316
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• 2021

Using directional antennas in wireless Ad hoc networks has many superiorities, including reducing interference, extending transmission range, and increasing space division multiplexing. However, directional transmission introduces two problems: deafness and directional hidden terminals problems. We observe that these problems result in saturation throughput disparity among the competing flows in directional CSMA/CA based Ad hoc networks and bring challenges for modeling the saturation throughput of the flows. In this article, we concentrate on how to model and analyze the saturation throughput disparity of different flows in directional CSMA/CA based Ad hoc networks. We first divide the collisions occurring in the transmission process into directional instantaneous collisions and directional persistent collisions. Then we propose a four-dimensional Markov chain to analyze the transmission state for a specific node. Our model has three different kinds of processes, namely back-off process, transmission process and freezing process. Each process contains a certain amount of continuous time slots which is defined as the basic time unit of the directional CSMA/CA protocols and the time length of each slot is fixed. We characterize the collision probabilities of the node by the one-step transition probability matrix in our Markov chain model. Accordingly, we can finally deduce the saturation throughput for each directional data stream and evaluate saturation throughput disparity for a given network topology. Finally, we verify the accuracy of our model by comparing the deviation of analytical results and simulation results.

• Journal of the Korea institute for structural maintenance and inspection
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• v.24 no.5
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• pp.77-85
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• 2020

In this study, the seismic fragility curve according to the boundary conditions is created for a two-pylon concrete cable-stayed bridge, and the effect of the boundary conditions on the seismic fragility of the target bridge is evaluated. An analysis model for the target bridge is constructed using Midas Civil, and a nonlinear time history analysis is performed by applying the fiber element, concrete and rebar material models. The boundary conditions between the pylon and the stiffened girder are classified into four types: rigid, unconstrained, pot bearing, and seismic isolation bearing, and the seismic fragility curves are created for each boundary condition. The plastic hinge section of the pylon, the connection part, and the cable are selected as weak members, and the earthquake vulnerability curve is created for them. As a result of the analysis, it is found that the seismic isolation bearing model shows the lowest damage probability in the pylon and the connection part, and the seismic fragility of the cable is less affected by the boundary conditions than other members.

• Korean Journal of Remote Sensing
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• v.38 no.5_3
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• pp.887-899
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• 2022

Drought caused by meteorological factors negatively affects vegetation in terrestrial ecosystems. In this study, the state in which meteorological drought affects vegetation was defined as the ecological drought of vegetation, and the ecological drought condition index of vegetation (EDCI-veg) was proposed to quantitatively monitor the degree of impact. EDCI-veg is derived from a copula-based bi-variate joint probability model between vegetation and meteorological drought information, and can be expressed numerically how affected the current vegetation condition was by the drought when the drought occurred. Comparing past meteorological drought events with their corresponding vegetation condition, the proposed index was examined, and it was confirmed that EDCI-veg could properly monitor the ecological drought of vegetation. In addition, it was possible to spatially identify ecological drought conditions by creating a high-resolution drought map using remote sensing data.

• Steel and Composite Structures
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• v.41 no.6
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• pp.831-850
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• 2021

Surface subsidence caused by mining subsidence has an impact on neighboring structures and utilities. In other words, subsurface voids created by mining or tunneling activities induce soil movement, exposing buildings to physical and/or functional destruction. Soil-structure is evaluated employing probability distribution laws to account for their uncertainty and complexity to estimate structural vulnerability. In this study, to investigate the displacement field and surface settlement profile caused by mining subsidence, on the basis of a Winklersoil model, analytical equations for the moment-rotation response ofsoil during mining induced ground movements are developed. To define the full static moment-rotation response, an equation for the uplift-yield state is constructed and integrated with equations for the uplift- and yield-only conditions. The constructed model's findings reveal that the inverse of the factor of safety (x) has a considerable influence on the moment-rotation curve. The maximal moment-rotation response of the footing is defined by X = 0:6. Despite the use of Winkler model, the computed moment-rotation response results derived from the literature were analyzed through the ELM-SVM hybrid of Extreme Learning Machine (ELM) and Support Vector Machine (SVM). Also, Monte Carlo simulations are used to apply continuous random parameters to assess the transmission of ground motions to structures. Following the findings of RMSE and R2, the results show that the choice of probabilistic laws of input parameters has a substantial impact on the outcome of analysis performed.

• Smart Structures and Systems
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• v.29 no.1
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• pp.181-193
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• 2022

Data-driven structural health monitoring (SHM) of civil infrastructure can be used to continuously assess the state of a structure, allowing preemptive safety measures to be carried out. Long-term monitoring of large-scale civil infrastructure often involves data-collection using a network of numerous sensors of various types. Malfunctioning sensors in the network are common, which can disrupt the condition assessment and even lead to false-negative indications of damage. The overwhelming size of the data collected renders manual approaches to ensure data quality intractable. The task of detecting and classifying an anomaly in the raw data is non-trivial. We propose an approach to automate this task, improving upon the previously developed technique of image-based pre-processing on one-dimensional (1D) data by enriching the features of the neural network input data with multiple channels. In particular, feature engineering is employed to convert the measured time histories into a 3-channel image comprised of (i) the time history, (ii) the spectrogram, and (iii) the probability density function representation of the signal. To demonstrate this approach, a CNN model is designed and trained on a dataset consisting of acceleration records of sensors installed on a long-span bridge, with the goal of fault detection and classification. The effect of imbalance in anomaly patterns observed is studied to better account for unseen test cases. The proposed framework achieves high overall accuracy and recall even when tested on an unseen dataset that is much larger than the samples used for training, offering a viable solution for implementation on full-scale structures where limited labeled-training data is available.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.45 no.4
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• pp.53-60
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• 2022

In a group-testing method, instead of testing a sample, for example, blood individually, a batch of samples are pooled and tested simultaneously. If the pooled test is positive (or defective), each sample is tested individually. However, if negative (or good), the test is terminated at one pooled test because all samples in the batch are negative. This paper considers a queueing system with a two-stage group-testing policy. Samples arrive at the system according to a Poisson process. The system has a single server which starts a two-stage group test in a batch whenever the number of samples in the system reaches exactly a predetermined size. In the first stage, samples are pooled and tested simultaneously. If the pooled test is negative, the test is terminated. However, if positive, the samples are divided into two equally sized subgroups and each subgroup is applied to a group test in the second stage, respectively. The server performs pooled tests and individual tests sequentially. The testing time of a sample and a batch follow general distributions, respectively. In this paper, we derive the steady-state probability generating function of the system size at an arbitrary time, applying a bulk queuing model. In addition, we present queuing performance metrics such as the offered load, output rate, allowable input rate, and mean waiting time. In numerical examples with various prevalence rates, we show that the second-stage group-testing system can be more efficient than a one-stage group-testing system or an individual-testing system in terms of the allowable input rates and the waiting time. The two-stage group-testing system considered in this paper is very simple, so it is expected to be applicable in the field of COVID-19.