• Title/Summary/Keyword: Kriging system

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A study on the correlation between the result of electrical resistivity survey and the rock mass classification values determined by the tunnel face mapping (전기비저항탐사결과와 터널막장 암반분류의 상관성 검토)

  • 최재화;조철현;류동우;김학규;서백수
    • Proceedings of the Korean Geotechical Society Conference
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    • 2003.03a
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    • pp.265-272
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    • 2003
  • In this study, the rock mass classification results from the face mapping and the resistivity inversion data are compared and analyzed for the reliability investigation of the determination of the rock support type based on the surface electrical survey. To get the quantitative correlation, rock engineering indices such as RCR(rock condition rating), N(Rock mass number), Q-system based on RMR(rock mass rating) are calculated. Kriging method as a post processing technique for global optimization is used to improve its resolution. The result of correlation analysis shows that the geological condition estimated from 2D electrical resistivity survey is coincident globally with the trend of rock type except for a few local areas. The correlation between the results of 3D electrical resistivity survey and the rock mass classification turns out to be very high. It can be concluded that 3D electrical resistivity survey is powerful to set up the reliable rock support type.

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Optimization of a SMES Magnet in the Presence of Uncertainty Utilizing Sampling-based Reliability Analysis

  • Kim, Dong-Wook;Choi, Nak-Sun;Choi, K.K.;Kim, Heung-Geun;Kim, Dong-Hun
    • Journal of Magnetics
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    • v.19 no.1
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    • pp.78-83
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    • 2014
  • This paper proposes an efficient reliability-based optimization method for designing a superconducting magnetic energy system in presence of uncertainty. To evaluate the probability of failure of constraints, samplingbased reliability analysis method is employed, where Monte Carlo simulation is incorporated into dynamic Kriging models. Its main feature is to drastically reduce the numbers of iterative designs and computer simulations during the optimization process without sacrificing the accuracy of reliability analysis. Through comparison with existing methods, the validity of the proposed method is examined with the TEAM Workshop Problem 22.

Spatiotemporal Location Fingerprint Generation Using Extended Signal Propagation Model

  • Kim, Hee-Sung;Li, Binghao;Choi, Wan-Sik;Sung, Sang-Kyung;Lee, Hyung-Keun
    • Journal of Electrical Engineering and Technology
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    • v.7 no.5
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    • pp.789-796
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    • 2012
  • Fingerprinting is a widely used positioning technology for received signal strength (RSS) based wireless local area network (WLAN) positioning system. Though spatial RSS variation is the key factor of the positioning technology, temporal RSS variation needs to be considered for more accuracy. To deal with the spatial and temporal RSS characteristics within a unified framework, this paper proposes an extended signal propagation mode (ESPM) and a fingerprint generation method. The proposed spatiotemporal fingerprint generation method consists of two algorithms running in parallel; Kalman filtering at several measurement-sampling locations and Kriging to generate location fingerprints at dense reference locations. The two different algorithms are connected by the extended signal propagation model which describes the spatial and temporal measurement characteristics in one frame. An experiment demonstrates that the proposed method provides an improved positioning accuracy.

Predicting the likelihood of impaired stream segments using Geographic Information System on Abandoned Mine Land in Gangwon Province

  • Lee, Ju-Young;Yang, Jung-Suk;Choi, Jae-Young
    • Proceedings of the Korea Water Resources Association Conference
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    • 2007.05a
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    • pp.1081-1083
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    • 2007
  • The study in river basin has been performed for the identify water quality impaired stream segments, to create a priority ranking of those segments, and to calculate the heavy metal ion distribution for each impaired segment based on chemical and physical water quality standards. Two methods for modeling the potential area-specific heavy metal distribution are pursued in this study. First, a novel approach focuses on distance. Heavy metal distribution can be associated with a particular small geographic area. Based on the derived estimates an distribution map can be generated. Second, the approach is used the near watershed by means of kriging interpolation algorithm. These approaches provide an alternative distribution mapping of the area. The exposure estimates from both of these modeling methods are then compared with other environmental monitoring data. A GIS-based model will be used to mimic the hierarchical stream structure and processes found in natural watershed. Specifically, the relationship between landscape variables and reach scale habitat conditions most influential found in the Abandoned mine will be explored.

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Development of Spatial Statistical Downscaling Method for KMA-RCM by Using GIS (GIS를 활용한 KMA-RCM의 규모 상세화 기법 개발 및 검증)

  • Baek, Gyoung-Hye;Lee, Moun-Gjin;Kang, Byung-Jin
    • Journal of the Korean Association of Geographic Information Studies
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    • v.14 no.3
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    • pp.136-149
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    • 2011
  • The aim of this study is to develop future climate scenario by downscaling the regional climate model (RCM) from global climate model (GCM) based on IPCC A1B scenario. To this end, the study first resampled the KMA-RCM(Korea meteorological administration-regional climate model) from spatial resolution of 27km to 1km. Second, observed climatic data of temperature and rainfall through 1971-2000 were processed to reflect the temperature lapse rate with respect to the altitude of each meteorological observation station. To optimize the downscaled results, Co-kriging was used to calculate temperature lapse-rate; and IDW was used to calculate rainfall lapse rate. Fourth, to verify results of the study we performed correlation analysis between future climate change projection data and observation data through the years 2001-2010. In this study the past climate data (1971-2000), future climate change scenarios(A1B), KMA-RCM(Korea meteorological administration-regional climate model) results and the 1km DEM were used. The research area is entire South Korea and the study period is from 1971 to 2100. Monthly mean temperatures and rainfall with spatial resolution of 1km * 1km were produced as a result of research. Annual average temperature and precipitation had increased by $1.39^{\circ}C$ and 271.23mm during 1971 to 2100. The development of downscaling method using GIS and verification with observed data could reduce the uncertainty of future climate change projection.

Application of Geostatistical Methods to Groundwater Flow Analysis in a Heterogeneous Anisotropic Aquifer (불균질.이방성 대수층의 지하수 유동분석에 지구통계기법의 응용)

  • 정상용;유인걸;윤명재;권해우;허선희
    • The Journal of Engineering Geology
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    • v.9 no.2
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    • pp.147-159
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    • 1999
  • Geostatistical methods were used for the groundwater flow analysis in a heterogeneous anisotropic aquifer. This study area is located at Sonbul-myeon in Hampyong-gun of Cheonnam Province which is a hydrogeological project area of KORES(Korea Resources Cooperation). Linear regression analysis shows that the topographic elevation and groundwater level of this area have very high correlation. Groundwater-level contour maps produced by ordinary kriging and cokringing have large differences in mountain areas, but small differences in hill and plain areas near the West Sea. Comparing two maps on the basis of an elevation contour map, a groundwater-level contour map using cokriging is more accurate. Analyzing the groundwater flow on two groundwater-level contour maps, the groundwater of study area flows from the high mountain areas to the plain areas near the West Sea. To verify the enffectiveness of geostatistical methods for the groundwater flow analysis in a heterogeneous anisotropic aquifer, the flow directions of groundwater were measured at two groundwater boreholes by a groundwater flowmeter system(model 200 $GeoFlo^{R}$). The measured flow directions of groundwater almost accord with those estimated on two groundwater-level contour maps produced by geostatistical methods.

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Optimal Shape of Blunt Device for High Speed Vehicle

  • Rho, Joo-Hyun;Jeong, Seongmin;Kim, Kyuhong
    • International Journal of Aeronautical and Space Sciences
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    • v.17 no.3
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    • pp.285-295
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    • 2016
  • A contact strip shape of a high speed train pantograph system was optimized with CFD to increase the aerodynamic performance and stability of contact force, and the results were validated by a wind tunnel test. For design of the optimal contact strip shape, a Kriging model and genetic algorithm were used to ensure the global search of the optimal point and reduce the computational cost. To enhance the performance and robustness of the contact strip for high speed pantograph, the drag coefficient and the fluctuation of the lift coefficient along the angle of attack were selected as design objectives. Aerodynamic forces were measured by a load cell and HWA (Hot Wire Anemometer) was used to measure the Strouhal number of wake flow. PIV (Particle Image Velocimetry) was adopted to visualize the flow fields. The optimized contact strip shape was shown a lower drag with smaller fluctuation of vertical lift force than the general shaped contact strip. And the acoustic noise source strength of the optimized contact strip was also reduced. Finally, the reduction amount of drag and noise was assessed when the optimized contact strip was applied to three dimensional pantograph system.

An Approximation Method in Collaborative Optimization for Engine Selection coupled with Propulsion Performance Prediction

  • Jang, Beom-Seon;Yang, Young-Soon;Suh, Jung-Chun
    • Journal of Ship and Ocean Technology
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    • v.8 no.2
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    • pp.41-60
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    • 2004
  • Ship design process requires lots of complicated analyses for determining a large number of design variables. Due to its complexity, the process is divided into several tractable designs or analysis problems. The interdependent relationship requires repetitive works. This paper employs collaborative optimization (CO), one of the multidisciplinary design optimization (MDO) techniques, for treating such complex relationship. CO guarantees disciplinary autonomy while maintaining interdisciplinary compatibility due to its bi-level optimization structure. However, the considerably increased computational time and the slow convergence have been reported as its drawbacks. This paper proposes the use of an approximation model in place of the disciplinary optimization in the system-level optimization. Neural network classification is employed as a classifier to determine whether a design point is feasible or not. Kriging is also combined with the classification to make up for the weakness that the classification cannot estimate the degree of infeasibility. For the purpose of enhancing the accuracy of a predicted optimum and reducing the required number of disciplinary optimizations, an approximation management framework is also employed in the system-level optimization.

Thermal conductivity prediction model for compacted bentonites considering temperature variations

  • Yoon, Seok;Kim, Min-Jun;Park, Seunghun;Kim, Geon-Young
    • Nuclear Engineering and Technology
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    • v.53 no.10
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    • pp.3359-3366
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    • 2021
  • An engineered barrier system (EBS) for the deep geological disposal of high-level radioactive waste (HLW) is composed of a disposal canister, buffer material, gap-filling material, and backfill material. As the buffer fills the empty space between the disposal canisters and the near-field rock mass, heat energy from the canisters is released to the surrounding buffer material. It is vital that this heat energy is rapidly dissipated to the near-field rock mass, and thus the thermal conductivity of the buffer is a key parameter to consider when evaluating the safety of the overall disposal system. Therefore, to take into consideration the sizeable amount of heat being released from such canisters, this study investigated the thermal conductivity of Korean compacted bentonites and its variation within a temperature range of 25 ℃ to 80-90 ℃. As a result, thermal conductivity increased by 5-20% as the temperature increased. Furthermore, temperature had a greater effect under higher degrees of saturation and a lower impact under higher dry densities. This study also conducted a regression analysis with 147 sets of data to estimate the thermal conductivity of the compacted bentonite considering the initial dry density, water content, and variations in temperature. Furthermore, the Kriging method was adopted to establish an uncertainty metamodel of thermal conductivity to verify the regression model. The R2 value of the regression model was 0.925, and the regression model and metamodel showed similar results.

A Study on Optimal Design for Linear Electromagnetic Generator of Electricity Sensor System using Vibration Energy Harvesting (진동에너지 하베스팅을 이용한 전력감지시스템용 리니어 전자기 발전기에 관한 최적설계)

  • Cho, Seong Jin;Kim, Jin Ho
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.16 no.2
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    • pp.7-15
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    • 2017
  • Recently, an electricity sensor system has been installed and operated to prevent failures and accidents by identifying whether a transformer is normal in advance of failure. This electricity sensor system is able to both measure and monitor the transformer's power and voltage remotely and send information to a manager when unusual operation is discovered. However, a battery is required to operate power detection devices, and battery systems need ongoing management such as regular replacement. In addition, at a maintenance cost, occasional human resources and worker safety problems arise. Accordingly, we apply a linear electromagnetic generator using vibration energy from a transformer for an electric sensor system's drive in this research and we conduct optimal design to maximize the linear electromagnetic generator's power. We consider design variables using the provided design method from Process Integration, Automation, and Optimization (PIAnO), which is common tool from process integration and design optimization (PIDO). In addition, we analyze the experiment point from the design of the experiments using "MAXWELL," which is a common electromagnet analysis program. We then create an approximate model and conduct accuracy verification. Finally, we determine the optimal model that generates the maximum power using the proven approximate kriging model and evolutionary optimization algorithm, which we then confirm via simulation.