• Proceedings of the Korea Water Resources Association Conference
• /
• 2017.05a
• /
• pp.100-100
• /
• 2017

하천에 유입된 오염물질의 2차원 혼합거동은 하천 주흐름에 의한 이송현상과 유속 성분의 수심평균 값에 대한 공간적 편차로부터 야기되는 분산현상으로 설명 할 수 있다. 이는 3차원 이송확산 방정식으로부터 수심 적분된 2차원 이송-분산 방정식으로 수학적 유도가 가능하며, 수심방향으로 적분하는 과정에서 발생되는 농도의 분산항은 Taylor Dispersion 개념에 기초하여 종방향 및 횡방향의 2차원 분산계수로 표현된다. Fischer(1978)는 연직방향 유속분포로부터 2차원 분산계수를 추정하는 해석해를 수학적으로 유도하였으나, 실제 하천에서 정밀한 연직방향 유속분포를 계측하는 것은 많은 비용 및 노동력을 초래한다. 따라서 선행 연구자들은 2차원 혼합모형의 분산계수를 산정하고자 실험적 방법으로써 추적자실험을 수행하였다. 추적자실험은 추적자 물질을 수체에 주입한 후 농도의 변화를 관측함으로써 추적자물질이 하천에서 이송 및 분산되는 과정을 이해하는데 유용하다. 기존의 추적자실험은 고정된 위치에서 농도를 계측하여 시계열적인 농도의 변화를 관측한 후, 오염운 동결가정을 통해 종,횡방향 분산계수의 산정이 가능하지만, 오염물질 농도의 공간적 분포를 얻기에는 한계가 있다. 본 연구에서는 기존의 추적자실험법의 한계를 극복하고자 형광물질을 이용한 추적자실험을 수행함과 동시에 드론에 장착된 디지털카메라를 이용하여 항공영상을 취득 및 분석하여, 하천에 주입된 형광물질의 농도분포를 시공간적으로 추출하는 기법을 개발하고, 이를 바탕으로 오염물질의 2차원 혼합거동을 분석하였다. 본 실험은 한국건설기술연구원의 안동하천실험센터의 A3실험수로에서 수행되었으며, 실험수로는 평균 하폭 5 m, 평균 수심 0.44 m, 유량 $0.96m^3/s$의 실제 소규모 하천과 유사한 축척을 가지고 있다. 추적자물질은 Rhodamine WT 용액이 사용되었으며, 실험수로 내 설치된 15개의 형광광도계(YSI-600OMS)를 이용하여 농도를 측정하였다. 항공영상의 취득을 위해 이용된 드론은 DJI-Phantom 3 Professional 이며, 3840x2160의 해상도로 초당 30 frame의 동영상으로 취득되었다. 영상의 정합 및 좌표화를 위해 RTK-GPS를 이용하여 12개의 지상 기준점의 좌표를 취득한 후, 사영변환을 통해 영상좌표를 지상좌표로 변환하였다. 영상의 픽셀값을 농도장으로 변환하기 위해 각 RGB 밴드의 픽셀값을 통계적으로 분석하여 농도장으로 변환하였으며, 영상으로부터 얻은 농도장은 형광광도계에 의해 실측된 농도와 결정계수 0.9이상의 수준으로 정확도를 나타냈다.

• Journal of Korean Tunnelling and Underground Space Association
• /
• v.26 no.3
• /
• pp.209-222
• /
• 2024

The Earth Pressure Balance (EPB) shield Tunnel Boring Machine (TBM) is widely used for underground tunnel construction for its advantages, such as eliminating the need for additional facilities compared to the slurry shield TBM, which requires Slurry Treatment Plant (STP). During EPB shield TBM excavation, a soil conditioning technique is employed to enhance the physical properties of the excavated soil by injecting additives, thus broadening the range of applicable ground conditions to EPB shield TBMs. This study explored the use of xanthan gum, a type of biopolymer, as an alternative to the commonly used polymer additive. Biopolymers, derived from biological sources, are fully biodegradable. In contrast to traditional polymers such as polyacrylic acid, which contain environmentally harmful components, xanthan gum is gaining attention as an eco-friendly material due to its minimal toxicity and environmental impact. Test conditions with similar workability were established through slump tests, and the rheological characteristics were assessed using a laboratory pressurized vane shear test apparatus. The experiments demonstrated that, despite exhibiting similar workability, the peak strength in the flow curve decreased with increasing the content of xanthan gum. Consequently, a correlation between the xanthan gum content and peak strength was established. Replacing the traditional polymers with xanthan gum could enable stable EPB shield TBM operation by reducing equipment load, in addition to offering environmental benefits.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.13 no.2
• /
• pp.41-53
• /
• 2010

Traffic safety assessment is often accomplished by analyzing the number of crashes occurring in some geographic space over certain specific time duration. In this paper, we introduce a procedure that can efficiently analyze spatial and temporal changes in traffic crashes before-and-after implementation of a certain traffic controlling measure. For the analysis, crash frequency data before-and-after closing a major highway around St. Louis in Missouri was collected through Transportation Management System(TMS) database that is maintained by Missouri Department of Transportation (MoDOT). In order to identify any spatial and temporal pattern in crashes, each crash is pinpointed on a map using the dynamic segmentation in GIS. Then, the identified pattern is statistically confirmed using an analysis of variance table. The advantage of this approach is to easily assess spatial and temporal trend of crashes that are not readily attainable otherwise. The results from this study can possibly be applied in enhancing the highway safety assessment procedure. This paper also makes several suggestions for future development of a comprehensive transportation data system in Korea which is similar to MoDOT's TMS database.

• Proceedings of the Korean Society for Agricultural Machinery Conference
• /
• 2017.04a
• /
• pp.171-171
• /
• 2017

전산유체역학(CFD: Computational Fluid Dynamics)를 이용한 스마트팜 환경 내부의 정밀 제어 연구가 진행 중이다. 시계열 데이터의 난해한 동적 해석을 극복하기위해, 비선형 모델링 기법의 일종인 인공신경망을 이용하는 방안을 고려하였다. 선행 연구를 통하여 환경 데이터의 비선형 모델링을 위한 Tensorflow활용 방법이 하드웨어 가속 기능을 바탕으로 월등한 성능을 보임을 확인하였다. 그럼에도 오프라인 일괄(Offline batch)처리 방식의 한계가 있는 인공신경망 모델링 기법과 현장 보급이 불가능한 고성능 하드웨어 연산 장치에 대한 대안 마련이 필요하다고 판단되었다. CFD 해석을 위한 Solver로 SU2(http://su2.stanford.edu)를 이용하였다. 운영 체제 및 컴파일러는 1) Mac OS X Sierra 10.12.2 Apple LLVM version 8.0.0 (clang-800.0.38), 2) Windows 10 x64: Intel C++ Compiler version 16.0, update 2, 3) Linux (Ubuntu 16.04 x64): g++ 5.4.0, 4) Clustered Linux (Ubuntu 16.04 x32): MPICC 3.3.a2를 선정하였다. 4번째 개발환경인 병렬 시스템의 경우 하드웨어 가속는 OpenCL(https://www.khronos.org/opencl/) 엔진을 이용하고 저전력 ARM 프로세서의 일종인 옥타코어 Samsung Exynos5422 칩을 장착한 ODROID-XU4(Hardkernel, AnYang, Korea) SBC(Single Board Computer)를 32식 병렬 구성하였다. 분산 컴퓨팅을 위한 환경은 Gbit 로컬 네트워크 기반 NFS(Network File System)과 MPICH(http://www.mpich.org/)로 구성하였다. 공간 분해능을 계측 주기보다 작게 분할할 경우 발생하는 미지의 바운더리 정보를 정의하기 위하여 3차원 Kriging Spatial Interpolation Method를 실험적으로 적용하였다. 한편 병렬 시스템 구성이 불가능한 1,2,3번 환경의 경우 내부적으로 이미 존재하는 멀티코어를 활용하고자 OpenMP(http://www.openmp.org/) 라이브러리를 활용하였다. 64비트 병렬 8코어로 동작하는 1,2,3번 운영환경의 경우 32비트 병렬 128코어로 동작하는 환경에 비하여 근소하게 2배 내외로 연산 속도가 빨랐다. 실시간 CFD 수행을 위한 분산 컴퓨팅 기술이 프로세서의 속도 및 운영체제의 정보 분배 능력에 따라 결정된다고 판단할 수 있었다. 이를 검증하기 위하여 4번 개발환경에서 운영체제를 64비트로 개선하여 5번째 환경을 구성하여 검증하였다. 상반되는 결과로 64비트 72코어로 동작하는 분산 컴퓨팅 환경에서 단일 프로세서 기반 멀티 코어(1,2,3번) 환경보다 보다 2.5배 내외 연산속도 향상이 있었다. ARM 프로세서용 64비트 운영체제의 완성도가 낮은 시점에서 추후 성공적인 실시간 CFD 모델링을 위한 지속적인 검토가 필요하다.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.12 no.6
• /
• pp.571-576
• /
• 2002

There have been a lot of considerations dealing with improving the performance of neuro-fuzzy system. The studies on the neuro-fuzzy modeling have largely been devoted to two approaches. First is to improve performance index of system. The other is to reduce the structure size. In spite of its satisfactory result, it should be noted that these are difficult to extend to high dimensional input or to increase the membership functions. We propose a novel neuro-fuzzy system based on the efficient clustering method for initializing the parameters of the premise part. It is a very useful method that maintains a few number of rules and improves the performance. It combine the various algorithms to improve the performance. The Expectation-Maximization algorithm of Gaussian mixture model is an efficient estimation method for unknown parameter estimation of mirture model. The obtained parameters are used for fuzzy clustering method. The proposed method satisfies these two requirements using the Gaussian mixture model and neuro-fuzzy modeling. Experimental results indicate that the proposed method is capable of giving reliable performance.

• Journal of the Korean Association of Geographic Information Studies
• /
• v.20 no.1
• /
• pp.1-14
• /
• 2017

A land cover map provides basic information to help understand the current state of a region, but its utilization in the ecological research field has deteriorated due to limited temporal and spatial resolutions. The purpose of this study was to investigate the possibility of using a land cover map with data based on high resolution images acquired by UAV. Using the UAV, 10.5 cm orthoimages were obtained from the $2.5km^2$ study area, and land cover maps were obtained from object-based and pixel-based classification for comparison and analysis. From accuracy verification, classification accuracy was shown to be high, with a Kappa of 0.77 for the pixel-based classification and a Kappa of 0.82 for the object-based classification. The overall area ratios were similar, and good classification results were found in grasslands and wetlands. The optimal image segmentation weights for object-based classification were Scale=150, Shape=0.5, Compactness=0.5, and Color=1. Scale was the most influential factor in the weight selection process. Compared with the pixel-based classification, the object-based classification provides results that are easy to read because there is a clear boundary between objects. Compared with the land cover map from the Ministry of Environment (subdivision), it was effective for natural areas (forests, grasslands, wetlands, etc.) but not developed areas (roads, buildings, etc.). The application of an object-based classification method for land cover using UAV images can contribute to the field of ecological research with its advantages of rapidly updated data, good accuracy, and economical efficiency.

• Journal of the Institute of Electronics Engineers of Korea SP
• /
• v.43 no.1 s.307
• /
• pp.55-66
• /
• 2006

We propose a progressive image retrieval method based on an efficient combination of multiresolution color and torture features in wavelet transform domain. As a color feature, color autocorrelogram of the hue and saturation components is chosen. As texture features, BDIP and BVLC moments of the value component are chosen. For the selected features, we obtain multiresolution feature vectors which are extracted from all decomposition levels in wavelet domain. The multiresolution feature vectors of the color and texture features are efficiently combined by the normalization depending on their dimensions and standard deviation vector, respectively, vector components of the features are efficiently quantized in consideration of their storage space, and computational complexity in similarity computation is reduced by using progressive retrieval strategy. Experimental results show that the proposed method yields average $15\%$ better performance in precision vs. recall and average 0.2 in ANMRR than the methods using color histogram color autocorrelogram SCD, CSD, wavelet moments, EHD, BDIP and BVLC moments, and combination of color histogram and wavelet moments, respectively. Specially, the proposed method shows an excellent performance over the other methods in image DBs contained images of various resolutions.

• KSCE Journal of Civil and Environmental Engineering Research
• /
• v.36 no.6
• /
• pp.1023-1035
• /
• 2016

Suspended sediment concentration (SSC) is a crucial riverine parameter in terms that it can be utilized for analyzing sediment transport, stability assessment of river and structure and so on. However, in case of domestic, sediment discharge data are not enough because of using conventional sediment samplers. This study aimed at developing a practical technique for estimating suspended sediment concentration in high spatial and temporal resolution by building relationship between acoustic backscatter (or SNR) from H-ADCP with actually observed data using LISST-100X. In this regard, a dedicated correction algorithm was proposed particularly for the adapted H-ADCP (SonTek SL-3000). Then, a SNR-SSC relation was built based upon a real-scale field experiment, where both H-ADCP and LISST-100X were concurrently operated to observe SNR and SSC, respectively. The coefficient of determination for the developed regression equation of SNR-SSC relation was around 0.85~0.88, thereby the relation could be evaluated to be highly correlated. The result of this study might be potentially applied for real-time and simultaneous observation of SSC when H-ADCP could be applied.

• Tunnel and Underground Space
• /
• v.23 no.2
• /
• pp.150-159
• /
• 2013

It is generally well known that the stratification of thermal energy in heat stores can be improved by increasing the aspect ratio (the height-to-width ratio) of the stores. Accordingly, it will be desirable to apply a high aspect ratio so as to demonstrate the good thermal performance of heat stores. However, as the aspect ratio of a store increases, the height of the store become larger compared to its width, which may be unfavorable for the structural stability of the store. Therefore, to determine an optimum aspect ratio of heat stores, a quantitative mechanical stability assessment should be performed in addition to thermal performance evaluations. In the present study, we numerically investigated the mechanical stability of silo-shaped rock caverns for underground thermal energy storage at different aspect ratios. The applied aspect ratios ranged from 1 to 6 and the mechanical stability was examined based on factor of safety using a shear strength reduction method. The results from the present study showed that the factor of safety of rock caverns tended to decrease with the increase in aspect ratio and the stress ratio of the surrounding rock mass was influential to the stability of the caverns. In addition, the numerical results demonstrated that under the same conditions of rock mass properties and aspect ratio, mechanical stability could be improved by the reduction in cavern size (storage volume), which indicates that one can design high-aspect-ratio rock caverns by dividing a single large cavern into multiple small caverns.

• Korean Journal of Remote Sensing
• /
• v.15 no.2
• /
• pp.147-158
• /
• 1999

Remote sensing technique has offered better understanding of our environment for the decades by providing useful level of information on the landcover. In many applications using the remotely sensed data, digital image processing methodology has been usefully employed to characterize the features in the data and develop the models. Random field models, especially Markov Random Field (MRF) models exploiting spatial relationships, are successfully utilized in many problems such as texture modeling, region labeling and so on. Usually, remotely sensed imagery are very large in nature and the data increase greatly in the problem requiring temporal data over time period. The time required to process increasing larger images is not linear. In this study, the methodology to reduce the computational cost is investigated in the utilization of the Markov Random Field. For this, multiresolution framework is explored which provides convenient and efficient structures for the transition between the local and global features. The computational requirements for parameter estimation of the MRF model also become excessive as image size increases. A Bayesian approach is investigated as an alternative estimation method to reduce the computational burden in estimation of the parameters of large images.