• KIPS Transactions on Software and Data Engineering
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• 제12권3호
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• pp.133-140
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• 2023

The performance of lithium ion batteries depends on the usage environment and the combination ratio of cathode materials. In order to develop a high-performance lithium-ion battery, it is necessary to manufacture the battery and measure its performance while varying the cathode material ratio. However, it takes a lot of time and money to directly develop batteries and measure their performance for all combinations of variables. Therefore, research to predict the performance of a battery using an artificial intelligence model has been actively conducted. However, since measurement experiments were conducted with the same battery in the existing published battery data, the cathode material combination ratio was fixed and was not included as a data attribute. In this paper, we define a training data model required to develop an artificial intelligence model that can predict battery performance according to the combination ratio of cathode materials. We analyzed the factors that can affect the performance of lithium-ion batteries and defined the mass of each cathode material and battery usage environment (cycle, current, temperature, time) as input data and the battery power and capacity as target data. In the battery data in different experimental environments, each battery data maintained a unique pattern, and the battery classification model showed that each battery was classified with an error of about 2%.

• Journal of the Korean Geotechnical Society
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• 제38권3호
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• pp.35-42
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• 2022

The N-value from the Standard Penetration Test (SPT), which is one of the representative in-situ test, is an important index that provides basic geological information and the depth of the bearing layer for the design of geotechnical structures. In the aspect of time and cost-effectiveness, there is a need to carry out a representative sampling test. However, the various variability and uncertainty are existing in the soil layer, so it is difficult to grasp the characteristics of the entire field from the limited test results. Thus the spatial interpolation techniques such as Kriging and IDW (inverse distance weighted) have been used for predicting unknown point from existing data. Recently, in order to increase the accuracy of interpolation results, studies that combine the geotechnics and deep learning method have been conducted. In this study, based on the SPT results of about 22,000 holes of ground survey, a comparative study was conducted to predict the depth of the bearing layer using deep learning methods and IDW. The average error among the prediction results of the bearing layer of each analysis model was 3.01 m for IDW, 3.22 m and 2.46 m for fully connected network and PointNet, respectively. The standard deviation was 3.99 for IDW, 3.95 and 3.54 for fully connected network and PointNet. As a result, the point net deep learing algorithm showed improved results compared to IDW and other deep learning method.

• Korea Trade Review
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• 제43권4호
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• pp.155-175
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• 2018

This study estimates the technical efficiency and total factor productivity(TFP) of and analyzes the relationship between TFP and exports for Korean manufacturing companies from 2000 to 2016. Specially, TFP is decomposed into Technical Change(TC), Technical Efficiency Change (TEC), and Sale Effect(SE), and compared between large and small enterprises. First, in the case of technical efficiency, the Korean economy has been very vulnerable to external shocks, such as the sharp decline following the 2008 financial crisis. The efficiency of the electronics, automobile, and machinery sectors is low and needs to be improved. In addition, the technological efficiency of large enterprises is higher than that of SMEs in most manufacturing sub-sectors except for non-ferrous metals. In the case of TFP, most changes are due to TC, and the effective combination of labor, capital and the effect of scale have little effect, suggesting that improvement of internal structure is urgent. In addition, volatility due to the impact of the financial crisis in 2008 was much larger in SMEs than in large companies, so external economic impacts are more greater for SMEs than large enterprises. The relationship between TFP decomposition factors and exports shows that TC has a positive effect only on exports of SMEs. Therefore, in order to increase exports, in the case of SMEs, R&D support to promote technological development is needed. In the case of large companies, it is necessary to establish differentiated strategies for each export market, competitor company, and item to link efficiency and scale effect of exports.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제30권3A호
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• pp.193-200
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• 2010

Structural design requires simultaneously to ensure safety by considering quantitatively uncertainties in the applied loadings, material properties and fabrication error and to maximize economical efficiency. As a solution, system reliability-based design optimization (SRBDO), which takes into consideration both uncertainties and economical efficiency, has been extensively researched and numerous attempts have been done to apply it to structural design. Contrary to conventional deterministic optimization, SRBDO involves the evaluation of component and system probabilistic constraints. However, because of the complicated algorithm for calculating component reliability indices and system reliability, excessive computational time is required when the large-scale finite element analysis is involved in evaluating the probabilistic constraints. Accordingly, an algorithm for SRBDO exhibiting improved stability and efficiency needs to be developed for the large-scale problems. In this study, a more stable and efficient SRBDO based on the performance measure approach (PMA) is developed. PMA shows good performance when it is applied to reliability-based design optimization (RBDO) which has only component probabilistic constraints. However, PMA could not be applied to SRBDO because PMA only calculates the probabilistic performance measure for limit state functions and does not evaluate the reliability indices. In order to overcome these difficulties, the decoupled algorithm is proposed where RBDO based on PMA is sequentially performed with updated target component reliability indices until the calculated system reliability index approaches the target system reliability index. Through a mathematical problem and ten-bar truss problem, the proposed method shows better convergence and efficiency than other approaches.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제28권6A호
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• pp.835-842
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• 2008

The response surface method (RSM) is widely adopted for the structural reliability analysis because of its numerical efficiency. However, the RSM is still time consuming for large-scale applications and sometimes shows large errors in the calculation of sensitivity of reliability index with respect to random variables. Therefore, this study proposes a new RSM in which moving least squares (MLS) approximation is applied. Least squares approximation generally used in the common RSM gives equal weight to the coefficients of the response surface function (RSF). On the other hand, The MLS approximation gives higher weight to the experimental points closer to the design point, which yields the RSF more similar to the limit state at the design point. In the procedure of the proposed method, a linear RSF is constructed initially and then a quadratic RSF is formed using the axial experimental points selected from the reduced region where the design point is likely to exist. The RSF is updated successively by adding one more experimental point to the previously sampled experimental points. In order to demonstrate the effectiveness of the proposed method, mathematical problems and ten-bar truss are considered as numerical examples. As a result, the proposed method shows better accuracy and computational efficiency than the common RSM.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제30권5B호
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• pp.459-469
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• 2010

This study is to develop a grid-based daily runoff model considering seasonal vegetation canopy condition. The model simulates the temporal and spatial variation of runoff components (surface, interflow, and baseflow), evapotranspiration (ET) and soil moisture contents of each grid element. The model is composed of three main modules of runoff, ET, and soil moisture. The total runoff was simulated by using soil water storage capacity of the day, and was allocated by introducing recession curves of each runoff component. The ET was calculated by Penman-Monteith method considering MODIS leaf area index (LAI). The daily soil moisture was routed by soil water balance equation. The model was evaluated for 930 $km^2$ Yongdam watershed. The model uses 1 km spatial data on landuse, soil, boundary, MODIS LAI. The daily weather data was built using IDW method (2000-2008). Model calibration was carried out to compare with the observed streamflow at the watershed outlet. The Nash-Sutcliffe model efficiency was 0.78~0.93. The watershed soil moisture was sensitive to precipitation and soil texture, consequently affected the streamflow, and the evapotranspiration responded to landuse type.

• KSCE Journal of Civil and Environmental Engineering Research
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• 제29권1A호
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• pp.31-43
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• 2009

In this study, the numerical method is presented, which can consider the various train types and can solve the equations of motion for a vehicle-bridge interaction analysis by non-iteration procedure through formulating the coupled equations of motion. The coupled equations of motion for the vehicle-bridge interaction are solved by the Newmark ${\beta}$ of a direct integration method, and by composing the effective stiffness matrix and the effective force vector according to a analysis step, those can be solved with the same manner of the solving procedure of equilibrium equations in static analysis. Also, the effective stiffness matrix is reconstructed by the Skyline method for increasing the analysis effectiveness. The Cholesky's matrix decomposition scheme is applied to the analysis procedure for minimizing the numerical errors that can be generated in directly calculating the inverse matrix. The equations of motion for the conventional trains are derived, and the numerical models of the conventional trains are idealized by a set of linear springs and dashpots with 16 degrees of freedom. The bridge models are simplified by the 3 dimensional space frame element which is based on the Euler-Bernoulli theory. The rail irregularities of vertical and lateral directions are generated by the PSD functions of the Federal Railroad Administration (FRA). The results of the vehicle-bridge interaction analysis are verified by the experimental results for the railway plate girder bridges of a span length with 12 m, 18 m, and the experimental and analytical data are applied to the low pass filtering scheme, and the basis frequency of the filtering is a 2 times of the 1st fundamental frequency of a bridge bending.

• Proceedings of the Korea Water Resources Association Conference
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• 한국수자원학회 2022년도 학술발표회
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• pp.41-41
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• 2022

홍수는 단기간의 사상이다. 평상시 유량은 일단위로 연속유량이라 한다. 홍수해석은 사상 모형을 이용하고, 물 이용의 용수계획에서는 연속 모형에 의한다. 평상시 유량을 홍수처럼 10분, 30분, 60분 단위로 해석할 수 있으면 여러 가지로 편리하다. 홍수기에는 홍수와 이수를 동시에 분석할 수 있는 이점이 있다. 평상시에는 수문자료가 생성되는 기본단위가 10분, 60분이기 때문에 이와 일치하여 유량을 해석할 수 있는 이점이 있다. 특히 저수지에서는 운영자료가 저수율 자료만 관리되고 있는 현실을 감안하면, 연속 홍수모의의 필요성은 매우 높다. 다목적댐도 그 편의성은 말로 형용할 수 없는 수준이다. 홍수모의는 첨두유량도 중요하고, 전체 누적유량도 중요하다. 여기서는 당초 일 단위로 개발된 ONE 모형으로 연속 홍수모의의 가능성을 타진했다. 모형의 검증은 홍수사상 마다 훨씬 긴 장기간의 댐의 유입량, 저수량 오차로 실시했다. 유입량이 누적되면 저수량이 되기 때문에 저수량을 비교하면 확실한 검증 방법이 된다. 유역면적 930.0km², 총저수량 8억1,500만m³인 용담댐과 유역면적 218.80km², 유효저수량 3,498만m³인 탑정지를 대상으로 60단위의 장기간 연속 홍수모의 결과를 제시한다. 첫째, 용담댐에 대해 2020년 3월1일부터 6월30일까지 연속유입량을 모의한 결과(ONE모형 매개변수 α=3.18), 면적우량은 최대 12.5mm, 총 371.2mm(3억4,522만m³)였고, 유입량은 최대 1,363.0m³/s, 총 1억8,326만m³로 유출률 53.1%였다, 관측 유입량은 최대 766.1m³/s, 총 2억9,152만m³로 유출률 84.4%로 나타났다. 관측 유입량이 높은 것으로 평가했는데 그 이유는 산정된 유입량이 넓은 수면적에서 오는 음유입량이 발생하는데 이를 0으로 처리하고, 음의 누적 값이 전체유량에 더해지는 계산의 한계에서 비롯한다. 이는 현실적 제한이며, 개선이 필요하다. 댐 수위로 검증한 결과는 관측수위는 EL.257.97~262.92m, 평균 EL.260.40m, 모의수위는 EL.257.22~262.88m, 평균 EL.260.02m로 나타났고, RMSE는 0.174, NSE는 0.959, R²는 0.968로 만족한 결과를 얻었다. 둘째, 탑정지에 대해 2020년 3월1일부터 6월30일까지 연속유입량을 모의한 결과(ONE모형 매개변수 α=3.18), 면적우량은 최대 18.5mm, 총 311.4mm(6,813만m³)였고, 유입량은 최대 187.8m³/s, 총 3,691만m³로 유출률 54.2%였다. 저수지 수위로 검증한 결과 관측수위는 EL.26.55~29.79m, 평균 EL.29.01m, 모의수위는 EL.26.16~29.92m, 평균 EL.29.07m로 나타났고, RMSE는 0.563, NSE는 0.877, R²는 0.943로 만족한 결과를 얻었다. 정리하면 2020년 4개월의 장기간 용담댐과 탑정지에 대한 1시간 간격의 연속 홍수모의의 결과는 그 활용 가능성이 충분하다고 말하고 있다. 이 결과로부터 평상시 댐과 저수지의 실시간 운영자료 검증 및 생산체제의 수문관측업무에 활용 가능한 것으로 평가했다.

• Korean Journal of Remote Sensing
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• 제39권5_2호
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• pp.849-858
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• 2023

Investigating disaster sites such as earthquakes and landslides involves significant risks due to potential secondary disasters like facility collapse. In situations where direct access is challenging, there is a need to develop methods for safely acquiring high-precision 3D disaster information using light detection and ranging (LiDAR) equipped drone survey systems. In this study, the feasibility of using drone LiDAR in disaster scenarios was examined, focusing on the collapse accident at Jeongja Bridge in Bundang-gu, Seongnam City, in April 2023. High-density point clouds for the accident bridge were collected, and the bridge's 3D terrain information was reconstructed and compared to the measurement performance of 10 ground control points. The results showed horizontal and vertical root mean square error values of 0.032 m and 0.055 m, respectively. Additionally, when compared to a point cloud generated using ground LiDAR for the same target area, a vertical difference of approximately 0.08 m was observed, but overall shapes showed minimal discrepancies. Moreover, in terms of overall data acquisition and processing time, drone LiDAR was found to be more efficient than ground LiDAR. Therefore, the use of drone LiDAR in disaster sites with significant risks allows for safe and rapid onsite investigations.

• Korean Journal of Remote Sensing
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• 제39권5_4호
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• pp.1155-1164
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• 2023

Currently, the National Forest Inventory (NFI) collects tree information by human, so the range and time of the survey are limited. Research is actively being conducted to extract tree information from a large area using aerial Light Detection And Ranging (LiDAR) and aerial photographs, but it does not reflect the characteristics of forest areas in Korea because it is conducted in areas with wide tree spacing or evenly spaced trees. Therefore, this study proposed a methodology for generating Digital Surface Model (DSM), Digital Elevation Model (DEM), and Canopy Height Model (CHM) images using aerial LiDAR, extracting the tree height through the local Maxima, and calculating the Diameter at Breath Height (DBH) through the DBH-tree height formula. The detection accuracy of trees extracted through the proposed methodology was 88.46%, 86.14%, and 84.31%, respectively, and the Root Mean Squared Error (RMSE) of DBH calculated based on the tree height formula was around 5cm, confirming the possibility of using the proposed methodology. It is believed that if standardized research on various types of forests is conducted in the future, the scope of automation application of the manual national forest resource survey can be expanded.