• Journal of the Korea Society of Computer and Information
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• v.28 no.8
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• pp.95-101
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• 2023

Colmap is one of the innovative artificial intelligence technologies, highly effective as a tool in 3D reconstruction tasks. Moreover, it excels at constructing intricate 3D models by utilizing images and corresponding metadata. Colmap generates 3D models by merging 2D images, camera position data, depth information, and so on. Through this, it achieves detailed and precise 3D reconstructions, inclusive of objects from the real world. Additionally, Colmap provides rapid processing by leveraging GPUs, allowing for efficient operation even within large data sets. In this paper, we have presented a method of collecting 2D images of traditional Korean towers and reconstructing them into 3D models using Colmap. This study applied this technology in the restoration process of traditional stone towers in South Korea. As a result, we confirmed the potential applicability of Colmap in the field of cultural heritage restoration.

• Smart Structures and Systems
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• v.30 no.4
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• pp.339-351
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• 2022

Evaluating the current condition of existing structures is of primary importance for economic and safety reasons. This can be addressed by Structural System Identification (SSI). A reliable static SSI depends on well-designed sensor configuration and loading cases, as well as efficient parameter estimation algorithms. Static SSI by the Measurement Error-Minimizing Observability Method (MEMOM) is a model-based deterministic static SSI method that could estimate structural parameters from static responses. In the current state of the art, this method is only applicable when structures are subjected to one loading case. This might lead to lack of information in some local regions of the structure (such as the null curvatures zones). To address this issue, the SSI by MEMOM using multiple loading cases is proposed in this work. Observability equations obtained from different loading cases are concatenated simultaneously and an optimization procedure is introduced to obtain the estimations by minimizing the discrepancy between the predicted response and the measured one. In addition, a Genetic-Algorithm (GA)-based Optimal Sensor Placement (OSP) method is proposed to tackle the OSP problem under multiple static loading cases for the very first time. In this approach, the Fisher Information Matrix (FIM)'s determinant is used as the metric of the goodness of sensor configurations. The numerical examples of a 3-span continuous bridge and a 13-story frame, are analyzed to validate the applicability of the extended SSI by MEMOM and the GA-based OSP method.

• Korean Journal of Agricultural Science
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• v.48 no.4
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• pp.831-842
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• 2021

Accurate measurements of feed energy values have a positive effect on the control of feed intake for animals, the formation of prices, and on economic profits. However, few studies have attempted to measure the energy values of domestic roughages and to validate an energy value prediction model. The purpose of this study is to build a database through measurements of the nutrient digestibility and digestible energy results of roughages used in Korea and to evaluate the domestic applicability of the National Research Council (NRC) estimation model. Oat hay, annual ryegrass, tall fescue, barnyard millet, and concentrates for beef cattle were used in the test. As a result of an in vivo digestibility trial, the total digestible nutrients (TDN) of oat hay, annual ryegrass, tall fescue, and barnyard millet were found to be 68.73, 55.02, 55.71, and 52.89%, respectively. As a result of comparing the estimated values using the NRC equation with the in vivo results, there was a difference of 3.55 to 6.84%P in the TDN. Inferred from this result, it is considered that TDN calculations using the NRC equation can be reasonable for the test feeds used in this study. These results can be utilized when revising the Korean Standard Tables of Feed Composition, which provides a comprehensive overview of Korean feed.

• The Journal of the Acoustical Society of Korea
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• v.41 no.2
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• pp.242-253
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• 2022

When the source waveform is unknown, the Green's function can be estimated by Ray-based Blind Deconvolution (RBD) based on the simple array signal processing. In previous papers, RBD was successfully demonstrated using simulation and experiments in shallow water environment. In this paper, we investigate the applicability of RBD for a long-range communication (e.g., 30 km, 60 km, and 90 km) in a deep water environment (1,000 m ~), using experimental data conducted in the east of Pohang, South Korea, in October 2018. Data results are presented to demonstrate Green's function estimation of a communication signal (2.2 kHz ~ 2.9 kHz) using a 16-element, 42-m long vertical array. The results show that the Green's function estimated from RBD is comparable to that of matched filter result. Additional communication performance at a maximum range of 90 km will be also presented.

• Nuclear Engineering and Technology
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• v.55 no.6
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• pp.2112-2124
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• 2023

With the rise of economic and safety standards for nuclear reactors, new concepts of Gen-IV reactors and modular reactors showed more complex designs that challenge current tools for reactor physics analysis. A Monte Carlo (MC) two-step method was proposed in this work. This calculation scheme uses the continuous-energy MC method to generate multi-group cross-sections from heterogeneous models. The multi-group MC method, which can adapt locally-heterogeneous models, is used in the core calculation step. This calculation scheme is verified using a Gen-IV modular lead-based fast reactor (LFR) benchmark case. The influence of homogenized patterns, scatter approximations, flux separable approximation, and local heterogeneity in core calculation on simulation results are investigated. Results showed that the cross-sections generated using the 3D assembly model with a locally heterogeneous representation of control rods lead to an accurate estimation with less than 270 pcm bias in core reactivity, 0.5% bias in control rod worth, and 1.5% bias on power distribution. The study verified the applicability of multi-group cross-sections generated with the MC method for LFR analysis. The study also proved the feasibility of multi-group MC in core calculation with local heterogeneity, which saves 85% time compared to the continuous-energy MC.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.415-415
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• 2020

국내 농업용수 수요량 산정에 있어서 논벼 수요량은 수정 Penman (Modified Penman: MP) 방법에 의한 증발산량을 기반으로 산정하고 있으나, 최근 국제식량농업기구 (Food and Agriculture Organization of the United Nations: FAO) 및 국내 농진청 등에서는 Penman-Monteith (PM) 방법에 의한 증발산량 산정방법을 채택하고 있다. 따라서 본 연구에서는 논벼 수요량 산정에 있어 우리나라 실제 현장여건에 적합한 논벼 증발산량 산정 방법을 제안하고자 기존에 적용하고 있는 MP 방법과 최근에 국내외적으로 제안되고 있는 PM 방법에 의한 논벼 수요량 산정 결과를 실질적으로 벼 생산에 공급된 저수지 공급량 자료와 비교 분석을 통해 현장 적용성을 평가해 보았다. 이를 위해 본 연구에서는 농진청에서 PM 증발산량 작물계수를 도출한 현장실험지구를 포함하는 호남지역을 대상으로 저수지 100 만톤 이상의 한국농어촌공사 관리지역 중 농업용수 공급량 자료가 신뢰성 있는 대표지구를 선정하였다. 농업용수 실제 공급량 자료를 기반으로 두 증발산량에 의한 논벼 수요량 산정 결과를 비교 분석한 결과, MP 방법에 의한 수요량이 PM 방법에 의한 수요량 보다 높게 나타났으며, 따라서 MP 방법에 의한 수요량이 PM 방법에 의한 수요량 보다 농업용수 공급량과의 차이가 작게 나타나는 경향을 보였다. 대체적으로 강우량이 적은 지역에서 농업용수 공급량 및 논벼 수요량이 높게 나타났으며, 이러한 결과는 공급량과 수요량간의 관계에도 영향을 미쳐 강우량이 많은 지역에서 강우량이 적은 지역에 비해 농업용수 공급일수가 감소함으로써 공급량과 수요량과의 차이가 적어지는 경향을 보였다. 본 연구 결과로 농업용수 공급량을 기준으로 논벼 수요량 산정에 있어 증발산량 산정방법은 안정적인 농업용수 공급계획과 수리시설 설계에서의 이수안전도 확보차원에서 MP 방법을 채택하는 것이 더 바람직 할 것으로 사료된다. 추가적으로 논벼 수요량 산정은 증발산량 산정방법 외에도 유효우량 산정방법, 수로손실, 재배관리손실 등의 다양한 관련 인자들의 영향을 받기 때문에 증발산량 산정방법과 더불어 이들 인자들에 대해서도 종합적인 평가를 실시하여 논벼 수요량 산정 결과의 신뢰성 확보가 요구된다.

• Structural Engineering and Mechanics
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• v.86 no.6
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• pp.715-730
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• 2023

Broad studies have addressed the issue of structural element damage identification, however, rubber bearing, as a key component of load transmission between the superstructure and substructure, is essential to the operational safety of a bridge, which should be paid more attention to its health condition. However, regarding the limitations of the traditional bearing damage detection methods as well as few studies have been conducted on this topic, in this paper, inspired by the model updating-based structural damage identification, a two-stage bearing damage identification method has been proposed. In the first stage, we deduce a novel bearing damage localization indicator, called element relative MSE, to accurately determine the bearing damage location. In the second one, the prior knowledge of bearing damage localization is combined with sailfish optimization (SFO) to perform the bearing damage estimation. In order to validate the feasibility, a numerical example of a 5-span continuous beam is introduced, also the noise robustness has been investigated. Meanwhile, the effectiveness and engineering applicability are further verified based on an experimental simply supported beam and actual engineering of the I-40 Bridge. The obtained results are good, which indicate that the proposed method is not only suitable for simple structures but also can accurately locate the bearing damage site and identify its severity for complex structure. To summarize, the proposed method provides a good guideline for the issue of bridge bearing detection, which could be used to reduce the difficulty of the traditional bearing failure detection approach, further saving labor costs and economic expenses.

• Proceedings of the Korea Water Resources Association Conference
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• 2021.06a
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• pp.231-231
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• 2021

하천 및 하천시설물 관리 등을 위해서는 유역에서 하천으로 유출되는 유사량 파악이 필요하다. 현재 유사량측정은 하천에서 여러 개(3~7개)의 측선에서 부유사채취기를 이용하여 측정하여 농도를 분석하여 유사량을 산정하게 된다. 본 연구는 유량측정 기법 중 최근 자동유량측정기술에 활용하는 지표유속법(index velocity method)을 부유사량 측정에 적용하고 검토하였다. 지표법(index method) 적용 방법은 여러 개의 측선에서 측정된 부유사농도와 평균농도와의 관계를 분석하고, 평균농도와 가장 상관성이 높은 측선의 부유사농도를 지표 부유사농도로 설정하여 지표부유사 농도와 평균부유사농도와의 관계식을 개발하여 부유사량 산정에 활용하였다. 대상하천은 주천강에 위치한 영월군(주천교) 지점을 선정하였으며, 2020년 주요 홍수사상에서 27개의 부유사 측정성과를 확보하였다. 부유사 측정을 위하여 5개의 측선에서 부유사를 측정하였고, 부유사농도 규모는 2.20~373.20mg/ℓ이다. 평균부유사농도와 가장 상관성(상관계수 0.9988)이 높은 4번 측선의 부유사농도를 지표부유사농도로 설정하고 평균부유사농도와 지표부유사농도의 관계식을 개발하였다. 그 결과 지표관계식의 결정계수(R²)는 0.9977로 매우 높게 산정되었으며, 실측 평균부유사농도와 계산 평균부유사농도의 편차율은 평균 26.71%(0.60~103.26%)로 분석되었다. 편차율은 상대적으로 부유사농도가 낮은 성과에서 높았으며, 부유사농도가 10mg/ℓ 이상에서는 편차율이 14.81%로 1/2 가까이 줄어들었다. 즉 유량이 적은 경우 흐름 및 부유사가 하천의 일부구간으로 불규칙하게 편중되거나 흐름 전체적으로 확산되지 않아 편차율이 높게 산정되는 것으로 판단된다. 이러한 결과를 볼 때 홍수시 부유사농도의 지표법을 이용한 부유사량 산정이 가능 할 것으로 판단된다.

• Proceedings of the Korea Water Resources Association Conference
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• 2022.05a
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• pp.208-208
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• 2022

Recently, the frequency of abnormal weather due to complex factors such as global warming is increasing frequently. From the past rainfall patterns, it is evident that climate change is causing irregular rainfall patterns. This phenomenon causes difficulty in predicting rainfall and makes it difficult to prevent and cope with natural disasters, casuing human and property damages. Therefore, accurate rainfall estimation and rainfall occurrence time prediction could be one of the ways to prevent and mitigate damage caused by flood and drought disasters. However, rainfall prediction has a lot of uncertainty, so it is necessary to understand and reduce this uncertainty. In addition, when accurate rainfall prediction is applied to the rainfall-runoff model, the accuracy of the runoff prediction can be improved. In this regard, this study aims to increase the reliability of rainfall prediction by analyzing the uncertainty of the Korean rainfall ensemble prediction data and the outflow analysis model using the Limited Area ENsemble (LENS) and the Grid based Rainfall-runoff Model (GRM) models. First, the possibility of improving rainfall prediction ability is reviewed using the QM (Quantile Mapping) technique among the bias correction techniques. Then, the GRM parameter calibration was performed twice, and the likelihood-parameter applicability evaluation and uncertainty analysis were performed using R², NSE, PBIAS, and Log-normal. The rainfall prediction data were applied to the rainfall-runoff model and evaluated before and after calibration. It is expected that more reliable flood prediction will be possible by reducing uncertainty in rainfall ensemble data when applying to the runoff model in selecting behavioral models for user uncertainty analysis. Also, it can be used as a basis of flood prediction research by integrating other parameters such as geological characteristics and rainfall events.

• Journal of Wetlands Research
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• v.21 no.spc
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• pp.98-106
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• 2019

The coefficient and exponent of the MUSLE(Modified Universal Soil Loss Equation) runoff factor in the SWAT(Soil and Water Assessment Tool) model are 11.8 and 0.56 respectively, which are equally applied to the estimation of soil erosion regardless of land use. they could derive overestimation or underestimation of soil erosion, which can cause problems in the selection of soil erosion-vulnerable area and evaluation of reduction management. However, there are no studies about the estimation of coefficients and exponent for the MUSLE runoff factor by land use and their applicability to the SWAT model. Thus, in order to predict soil erosion and sediment behavior accurately through SWAT model, it is necessary to estimate the coefficient and exponent of the MUSLE runoff factor by land use and evaluate its applicability. In this study, the coefficient and exponent of MUSLE runoff factor by land use were estimated for Gaa-cheon Watershed, and the differences in soil erosion and sediment from SWAT model were analyzed. The coefficient and exponent of runoff factor estimated by this study well reflected the characteristics of soil erosion in domestic highland watershed. Therefore, in order to apply the MUSLE which developed based on observed data of US agricultural basin to the domestic watershed, it is considered that a sufficient modification and supplementation process for the coefficient and exponent of the MUSLE runoff factor depending on land use is necessary. The results of this study can be used as a basic data for selecting soil erosion vulnerable area in the non-point source management areas and establishing and evaluating soil erosion reduction management.