• KEPCO Journal on Electric Power and Energy
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• v.5 no.3
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• pp.157-163
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• 2019

K-BEMS System was introduced to reduce peak load and to save total energy of the 120 buildings that KEPCO headquarter and branch offices use. K-BEMS system is composed of PV, battery, and hybrid PCS. In this system, ESS, PV, lighting is used to save building energy based on demand prediction. Currently, neural network technique for short past data is applied to demand prediction, and fixed scheduling method by operator for ESS charging/discharging is used. To enhance this system, KEPCO research institute has carried out this K-BEMS research project for 3 years since January 2016. As the result of this project, we developed new real-time highly reliable building demand prediction technique with error free and optimized automatic ESS charging/discharging technique. Through several field test, we can certify the developed algorithm performance successfully. So we will describe the details in this paper.

• Geomechanics and Engineering
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• v.30 no.6
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• pp.503-515
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• 2022

The permeability coefficient is an essential parameter for the study of seepage flow in fractured rock mass. This paper discusses the feasibility and application value of using readily available RQD (rock quality index) data to estimate mine water inflow and grouting quantity. Firstly, the influence of different fracture frequencies on permeability in a unit area was explored by combining numerical simulation and experiment, and the relationship between fracture frequencies and pressure and flow velocity at the monitoring point in fractured rock mass was obtained. Then, the stochastic function generation program was used to establish the flow analysis model in fractured rock mass to explore the relationship between flow velocity, pressure and analyze the universal law between fracture frequency and permeability. The concepts of fracture width and connectivity are introduced to modify the permeability calculation formula and grouting formula. Finally, based on the on-site grouting water control example, the rock mass quality index is used to estimate the mine water inflow and the grouting quantity. The results show that it is feasible to estimate the fracture frequency and then calculate the permeability coefficient by RQD. The relationship between fracture frequency and RQD is in accordance with exponential function, and the relationship between structure surface frequency and permeability is also in accordance with exponential function. The calculation results are in good agreement with the field monitoring results, which verifies the rationality of the calculation method. The relationship between the rock mass RQD index and the rock mass permeability established in this paper can be used to invert the mechanical parameters of the rock mass or to judge the permeability and safety of the rock mass by using the mechanical parameters of the rock mass, which is of great significance to the prediction of mine water inflow and the safety evaluation of water inrush disaster management.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.125-125
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• 2020

European Space Agency's Sentinel-1 has an improved spatial and temporal resolution, as compared to previous satellite data such as Envisat Advanced SAR (ASAR) or Advanced Scatterometer (ASCAT). Thus, the assumption used for low-resolution retrieval algorithms used by ENVISAT ASAR or ASCAT is not applicable to Sentinel-1, because a higher degree of land surface heterogeneity should be considered for retrieval. The assumption of homogeneity over land surface is not valid any more. In this study, considering that soil roughness is one of the key parameters sensitive to soil moisture retrievals, various approaches are discussed. First, soil roughness is spatially inverted from Sentinel-1 backscattering over Yanco sites in Australia. Based upon this, Artificial Neural Networks data (feedforward multiplayer perception, MLP, Levenberg-Marquadt algorithm) are compared with Fractal approach (brownian fractal, Hurst exponent of 0.5). When using ANNs, training data are achieved from theoretical forward scattering models, Integral Equation Model (IEM). and Sentinel-1 measurements. The network is trained by 20 neurons and one hidden layer, and one input layer. On the other hand, fractal surface roughness is generated by fitting 1D power spectrum model with roughness spectra. Fractal roughness profile is produced by a stochastic process describing probability between two points, and Hurst exponent, as well as rms heights (a standard deviation of surface height). Main interest of this study is to estimate a spatial variability of roughness without the need of local measurements. This non-local approach is significant, because we operationally have to be independent from local stations, due to its few spatial coverage at the global level. More fundamentally, SAR roughness is much different from local measurements, Remote sensing data are influenced by incidence angle, large scale topography, or a mixing regime of sensors, although probe deployed in the field indicate point data. Finally, demerit and merit of these approaches will be discussed.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.26 no.6A
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• pp.1001-1011
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• 2006

It is a general agreement that exact statistical solutions can be found by a Monte Carlo technique. Due to difficulties, however, in the numerical generation of random fields, which satisfy not only the probabilistic distribution but the spectral characteristics as well, it is recognized as relatively difficult to find an exact response variability of a structural response. In this study, recognizing that the random field assumes a constant over the domain under consideration when the correlation distance tends to infinity, a semi-theoretical solution of response variability is proposed for general structures. In this procedure, the probability density function is directly used. It is particularly noteworthy that the proposed methodology provides response variability for virtually any type of probability density function, and has capability of considering correlations between multiple random variables.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1995.04a
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• pp.213-216
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• 1995

공사장의 건설기계 소음은 저주파 에너지를 많이 가지고 있기 때문에, 일단 소음이 발생되면 그 전파가 멀리까지 감쇄없이 진행하는 물리적 특징을 가지고 있으며 현실적으로 흡음재처리를 통한 소음방지효과는 저조한 실정이다. 특히, 선진국에서는 건설기계 등의 엄격한 소음 인증제도 실시로 인해 국내 일부 건설장비 생산제품이 외국에서 요구하는 소음규제치를 초과하기 때문에 저소음, 저진동 건설기계 설계 기술의 발전이 없으면, 향후 수출여건이 점차 어려워지고 있다. 이와같은 주변여건의 변화로 인해 건설기계를 생산하는 입체에서는 공사장 소음과 같은 저주파 에너지에 의해 지배 받는 소음문제를 효과적으로 저감시키기 위한 건설기계의 저소음, 저진동 설계의 필요성을 심각하게 인식하고 있는 실정이다. 건설기계중, 소음이 문제시되는 기계로는 지반정지공사, 기초공사, 콘크리트공사, 포장공사, 파괴 및 해체공사와 기타등 6가지가 있다. 이중에서 환경연구원의 연구결과에 따르면, 항타기, 브레이커 및 착암기가 높은 소음도를 나타내고 있다. 가장 높은 소음을 배출하고 있는 항타기는 기초 공사에 쓰이는 것으로써 지반 천공후 H빔을 싣는 디젤 항타기의 경우, 소음도가 107dBA를 보여주고 있다. 이 값은 기계로부터 7m 떨어진 거리에서 측정된 값이다. 또, 파괴 및 해제공사에 쓰이는 브레이커는 98dBA의 소음도를 보여주고 있다. 착암기는 작용원리에 따라 91-96dBA의 소음을 배출하고 있다. 본 연구에서는 건설기계중 소음이 높아 문제시 되고 있는 유압 브레이커의 저소음 설계기술개발에 관한 내용이다. 저소음 브레이커의 개발을 위해 소음에너지의 전달경로를 검토하고, 현실성있는 소음방지 대책을 제시하였다. 연구결과, 브레이커의 설계개량을 통해, 10dB의 소음저감효과를 볼 수 있어 만족스러운 결과를 도출할 수 있었다.타를 처리하기에는 부적절한 방법임이 널리 알려진 사실이다[3]. 최근에 Ben Mrad와 Fassois[4]는 신호에 잡음이 존재하여도 이를 잘 처리할 수 있는 확률적(stochastic) 방법을 개발하여 기존의 결정적 방법들과 그 결과를 비교하였다. 그러나, 개발된 방법은 응답 신호에 백색잡음(white noise)이 섞이는 특수한 경우에만 사용할 수 있게 만들어져서 이 방법의 실질적인 적용에는 어려움이 있다. 본 연구에서는 기존의 방법들의 단점을 극복할 수 있는 새로운 회귀적 모우드 변수 규명 방법을 개발하였다. 이는 Fassois와 Lee가 ARMAX모델의 계수를 효율적으로 추정하기 위하여 개발한 뱉치방법인 Suboptimum Maximum Likelihood 방법[5]를 기초로 하여 개발하였다. 개발된 방법의 장점은 응답 신호에 유색잡음이 존재하여도 모우드 변수들을 항상 정확하게 구할 수 있으며, 또한 알고리즘의 안정성이 보장된 것이다.. 여기서는 실험실 수준의 평 판모델을 제작하고 실제 현장에서 이루어질 수 있는 진동제어 구조물에 대 한 동적실험 및 FRS를 수행하는 과정과 동일하게 따름으로써 실제 발생할 수 있는 오차나 error를 실험실내의 차원에서 파악하여 진동원을 있는 구조 물에 대한 진동제어기술을 보유하고자 한다. 이용한 해마의 부피측정은 해마경화증 환자의 진단에 있어 육안적인 MR 진단이 어려운 제한된 경우에만 실제적 도움을 줄 수 있는 보조적인 방법으로 생각된다.ofile whereas relaxivity at high field is not affected by τS. On the other hand, the change in τV does not affect low field profile but strongly in fluences on both inflection

• Proceedings of the Korea Water Resources Association Conference
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• 2010.05a
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• pp.273-277
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• 2010

This research was performed to examine changes in the timing of the growth of crops along with changes in temperatures due tochanges and to analyze the change of water-supply-reliability by adding an analysis of the change of agricultural water supply patterns in the basin area of Miryang dam in Korea. Had-CM3 model from U.K. was the tool adopted for the GCM model, a stochastic, daily-meteorology-generation-model called LARS-WG was alsoused for downscaling and for the climate change scenario (A1B) which represents Korea's circumstances best. First of all, to calculate changes in the timing of the growth of crops during this period, the theory of GDD was applied. Except for the period of transplanting and irrigation, there was no choice but to find the proper accumulated temperature by comparing actual temperature data and the supply pattern of agricultural use due to limited temperature data. As a result, proper temperatures were found for each period. $400^{\circ}C$ for the preparation period of a nursery bed, $704^{\circ}C$ for a nursery bed's period, $1,295^{\circ}C$ for the rice-transplanting period, $1,744^{\circ}C$ for starting irrigation, and $3,972^{\circ}C$ for finishing irrigation. To analyze future agricultural supply patter changes, the A1B scenario of Had-CM3 model was adopted, and then Downscaling was conducted adopting LARS-WG. To conduct a stochastical analysis of LARS-WG, climate scenarios were generated for the periods 2011~2030, 2046~2065, 2080~2099 using the data of precipitation andMax/Min temperatures collected from the Miryang gauging station. Upon reviewing the result of the analysis of accumulated temperatures from 2011~2030, the supply of agricultural water was 10 days earlier, and in the next periods-2046~2065, 2080~2099 it also was 10 days earlier. With these results, it is assumed that the supply of agricultural water should be about 1 month ahead of the existing schedule to meet the proper growth conditions of crops. From the results of the agricultural water supply patterns should be altered, but the reliability of water supply becomes more favorable, which is caused from the high precipitation change. Furthermore, since the unique characteristics of precipitation in Korea, which has high precipitation in the summer, water-supply-reliability has a pattern that the precipitation in September could significantly affect the chances of drought the following winter and spring. It could be more risky to make changes to the constant supply pattern under these conditions due to the high uncertainty of future precipitation. Although, several researches have been conducted concerning climate changes, in the field of water-industry, those researches have been solely dependent on precipitation. Even so, with the high uncertainty of precipitation, it is difficult for it to be reflected in government policy. Therefore, research in the field of water-supply-patterns or evapotranspiration according to the temperature or other diverse effects, which has higher reliability on anticipation, could obtain more reliable results in the future and that could result in water-resource maintenance to be safer and a more advantageous environment.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.2
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• pp.141-148
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• 2016

The long-span bridges such as Incheon Bridge and Seohae Grand Bridge are located on the coastal region effected frequently by strong wind of typhoons. In order to ensure the wind-resistant performance of the structure, estimation of the proper design wind speed is very important. In this study, stochastic estimation of design wind speed incurred by typhoons is carried out. For this purpose, we first established probability distribution of climatological parameters such as central pressure depth, distance of closest approach, translation speed and heading to build statistical model of typhoons, which are employed in Monte Carlo simulation for hypothetical typhoons. Once a typhoon is generated with statistically justified parameters, wind speeds are estimated along its path using wind field model. Thousands of typhoons are generated and their peak wind speeds are utilized to establish the extreme wind speeds for different return period. The results are compared with design basic wind speeds in Korean Highway Bridge Design Code, showing that the present results agree well with similar studies while the existing code suggests higher design wind speed.

• The Journal of Engineering Geology
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• v.23 no.4
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• pp.447-455
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• 2013

A micro-mechanical pipe network model with the shape of a cube was developed to simulate the behavior of fluid flow through a porous medium. The fluid-flow mechanism through the cubic pipe network channels was defined mainly by introducing a well-known percolation theory (Stauffer and Aharony, 1994). A non-uniform flow generally appeared because all of the pipe diameters were allocated individually in a stochastic manner based on a given pore-size distribution curve and porosity. Fluid was supplied to one surface of the pipe network under a certain driving pressure head and allowed to percolate through the pipe networks. A percolation condition defined by capillary pressure with respect to each pipe diameter was applied first to all of the network pipes. That is, depending on pipe diameter, the fluid may or may not penetrate a specific pipe. Once pore pressures had reached equilibrium and steady-state flow had been attained throughout the network system, Darcy's law was used to compute the resultant permeability. This study investigated the sensitivity of network size to permeability calculations in order to find out the optimum network size which would be used for all the network modelling in this study. Mean pore size and pore size distribution curve obtained from field are used to define each of pipe sizes as being representative of actual oil sites. The calculated and measured permeabilities are in good agreement.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
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• v.10 no.5
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• pp.409-416
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• 2017

In this paper, we consider a framework of compressed sensing over finite fields. One measurement sample is obtained by an inner product of a row of a sensing matrix and a sparse signal vector. A recovery algorithm proposed in this study for sparse signals based probabilistic decoding is used to find a solution of compressed sensing. Until now compressed sensing theory has dealt with real-valued or complex-valued systems, but for the processing of the original real or complex signals, the loss of the information occurs from the discretization. The motivation of this work can be found in efforts to solve inverse problems for discrete signals. The framework proposed in this paper uses a parity-check matrix of low-density parity-check (LDPC) codes developed in coding theory as a sensing matrix. We develop a stochastic algorithm to reconstruct sparse signals over finite field. Unlike LDPC decoding, which is published in existing coding theory, we design an iterative algorithm using probability distribution of sparse signals. Through the proposed recovery algorithm, we achieve better reconstruction performance as the size of finite fields increases. Since the sensing matrix of compressed sensing shows good performance even in the low density matrix such as the parity-check matrix, it is expected to be actively used in applications considering discrete signals.

• Journal of Korean Society of Environmental Engineers
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• v.38 no.5
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• pp.236-241
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• 2016

This study conducted a screening-level ecological risk assessment for heavy metals in dredged sediment for recycling in terrestrial environment. Toxicological information of six heavy metals (i.e., Cu, Zn, Cd, Pb, Cr, and Ni) was collected from ECOTOX of US Environmental Protection Agency, and screened and qualified for the use in the screening-level ecological risk assessment. According to the number of terrestrial ecological receptors for which toxicological information is available, PNEC (Predicted No Effect Concentration) of each heavy metal was derived using either stochastic approach (for Cu, Zn, and Cd), or deterministic approach (for Pb, Cr, and Ni). Hazard quotients of the six heavy metals were derived for a field-collected dredged sediment using the PNEC derived and the PEC (Predicted Environmental Concentration) determined for the dredged sediment. The HQs of Cu, Zn, Cr, Pb and Ni were higher than unity indicating a possibility of ecological risk of the five heavy metals when the dredged sediment is applied in terrestrial environment. Accordingly, remediation processes or a higher-level ecological risk assessment would be needed for the recycling of the material.