• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.11a
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• pp.1-3
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• 2018

국제해사기구(IMO)의 황천 중 조종성능 유지를 위한 최소추진마력 기준 제정과 국제수조협회(ITTC)의 파도 중 조종성능 추정에 대한 관심이 증가하면서 파도 중 조종성능 추정기술에 대한 연구가 많이 수행되고 있다. 본 연구에서는 파도 중 조종성능을 추정하는 기법중 하나인 시뮬레이션 기법 중에서 조종운동만을 시뮬레이션하는 간이 시뮬레이션을 수행하였고, 시뮬레이션 결과를 검증하기 위하여 자유 항주시험결과가 존재하는 S-175 컨테이너선에 대한 시뮬레이션을 수행하여 비교하였다.

• Journal of Ocean Engineering and Technology
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• v.33 no.5
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• pp.421-426
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• 2019

The directivity of an underwater sound source should be measured in an acoustically open field such as a calm sea or lake, or an anechoic water tank facility. However, technical difficulties arise when practically implementing this in open fields. Signal processing-based techniques such as a sound intensity method and near-field acoustic holography have been adopted to overcome the problem, but these are inefficient in terms of acquisition and maintenance costs. This study established a simple directivity estimation technique with data acquisition, filtering, and analysis tools. A numerical simulation based on an acoustic radiosity method showed that the technique is practicable for sound source directivity estimation in a diffused reverberant acoustic field like a reverberant water tank.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1993.04a
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• pp.294-300
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• 1993

어떤 무기체계의 임무신뢰도분석에 베이지안기법을 사용하는데 있어 고장율이 주어졌을 때 고장간 시간이 지수분포를 따른다는 가정하에 이의 Conjugate Prior인 감마분포의 추정문제를 다룬다. 임무별 고장간시간에 대한 예측분포를 유도하였으며, 실제 측정된 기존의 임무별 고장간시간이 이 예측분포를 따른다는 전제하에 비선형 최소자승법을 이용하여 감마분포의 두 파라메터를 추정하는 방안을 제시하였다. 또한 대상 무기체계의 실제 고장자료를 이용하여 추정치를 구하였다.

• Journal of the Society of Naval Architects of Korea
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• v.31 no.3
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• pp.145-153
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• 1994

In the fabrication of welded built-up beams, longitudinal deformation occurs due to welding, and this obstructs improvement of productivity and quality. In this study, to estimate the deformation due to welding, a simplified thermal elasto-plastic analysis method is proposed and verified by experiments. From the results of the simplified analysis, it is clarified that deformation coefficients defined in this study are the function of fabrication parameters. Based on this simplified analysis, a method to simulate the fabrication procedures for the built-up beams can be developed.

• Proceedings of the Computational Structural Engineering Institute Conference
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• 2010.04a
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• pp.126-131
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• 2010

본 논문에서는 극지 빙해역을 운항하는 쇄빙선박이나 해양구조물에 작용하는 해빙의 재료특성을 계측할 수 있는 간이 실험 장비를 제작하였다. 극지 빙해역을 운항하는 쇄빙선박의 빙저항이나 해양구조물에 작용하는 빙하중을 추정하기 위해서 극지 현장에서 실규모의 시험을 수행하게 되는데, 저온과 얼음이라는 악조건을 극복하기 위한 빙역학 기술과 특수 장비가 필요하다. 국내에 한국해양연구원 MOERI 빙해수조가 완공됨에 따라 얼음의 특성을 고려한 모형빙 재료특성 시험용 계측장비가 일부 마련이 되었으나 빙해역 현장 시험에 대한 경험이 전무하며, 계측장비에 대한 지식과 기술 역시 확보되지 못한 실정이다. 본 연구에서는 차후 쇄빙연구선 ARAON호를 이용한 빙해역의 실선계측 시 해빙의 강도를 측정하기 위한 계측시스템 마련의 일환으로 시험편 획득을 위한 코어링 장비와, 해빙의 재료특성 중 1축 압축강도를 측정하기 위한 간이 압축시험기 그리고 얼음의 결정구조를 파악하기 위한 편광기를 제작하였다. 또한 극지 현장실험에 적용할 실험기법 확보를 위한 일련의 과정을 마련하기 위해 제작된 장비를 이용해 소양호에서 현장실험을 수행하였고 계측된 결과를 참고문헌과 비교해본 결과 유사한 값을 갖는 것을 확인할 수 있었다.

• The Journal of the Acoustical Society of Korea
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• v.42 no.3
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• pp.227-232
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• 2023

Underwater noise pollution has a significant impact on the marine environment. This study proposed a simple approach to estimate the acoustic radiation efficiency of structures with air bubble layers. The method considered the insertion loss caused by the air bubble layer through post-processing of numerical results, assuming that insertion loss is equivalent to attenuation as demonstrated by previous studies. The proposed approach was validated by comparing it with a fully coupled analysis for plate structure models. The commercial finite element program COMSOL Multiphysics was used for the acoustic-structure interaction analysis, and the acoustic characteristics of air bubble layer for the fully coupled analysis was simulated by on the Commander and Prosperetti theory. The trends indicated good agreement between the simple approach and the fully coupled analysis in terms of radiation efficiency. It is confirmed that the proposed method is providing insight into the principal mechanism of underwater noise reduction for the bubble layer on the wedge-shaped structure.

• Proceedings of the Korea Water Resources Association Conference
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• 2020.06a
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• pp.396-396
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• 2020

기후변화는 여러 수자원 문제를 야기하며, 특히 가뭄으로 인해 농업용 저수지의 물관리는 점점 중요해지고 있다. 여러 둑높이기 농업용 저수지 중 나주호는 수혜면적에 비해 유역면적이 작아 저수율관리에 어려움을 겪고 있다. 실제로 2017년과 2018년 가뭄이 발생함에 따라 저수율이 20 %까지 저하되었으며, 수혜구역내 간이 양수장, 양수 저류 등 가뭄대책이 시행되었다. 그럼에도 불구하고 나주호의 저수율이 회복되지 않아 단수를 실시하는 등 물관리에 어려움을 겪었다. 이 연구에서는 저수지인 나주호를 대상으로 기상자료, 나주호의 저수율, 공급량 자료를 바탕으로 CAT 모형을 적용 가뭄년도의 유입량 변화를 추정하였다. 검보정의 경우 CAT 3.0 버전에 포함된 SCE-UA 최적화기법을 이용하였다. 그 결과, 2008년부터 2019년까지의 평균 연간 유입량은 6,549 만㎥으로 분석되었으며, 평균 연간 유출율은 48 %로 조사되었다. 하지만, 가뭄이 발생하였던 2017년도의 경우 평균 연간 유입량이 2,070 만㎥, 유출율은 27 %로 조사되었다.

• The Journal of Engineering Geology
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• v.25 no.2
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• pp.189-199
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• 2015

Our country's leading granite weathered soil of the ground slope failures that occur in cutting slope most cases, it does not require in-depth to the shear strength most of the surface layer is affected by weathering (1~2 m) at a shallow depth close to the ground, it is important to identify the reliability. Based on the result obtained in actual field investigation, the field slope type was classified by each type of wedge slope, Infinite slope, finite slope -I and finite slope -II, and the slope stability was examined respectively. In addition, using the numerical analysis results, the relationship between the slope inclination angle and safety factor was analyzed and it tried to offer basic data to which the stability in the field slope was able to be estimated by analyzing the safety factor change of the slope according to the slope type. In this study, classified into four types of natural slope, safety factor estimation method by slope types is proposed through the numerical analysis. However, some limit exists in generalizing in this research because it does not test various case studies. Therefore, the case study of a wide range of various sypes to assess the safety of various types slope can be made, accommodate a wide range of field conditions reasonable risk evaluation criteria may be derived.

• Journal of Intelligence and Information Systems
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• v.27 no.1
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• pp.177-190
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• 2021

Due to the development of the fourth industrial revolution technology, efforts are being made to improve areas that humans cannot handle by utilizing artificial intelligence techniques such as machine learning. Although on-demand production companies also want to reduce corporate risks such as delays in delivery by predicting total production time for orders, they are having difficulty predicting this because the total production time is all different for each order. The Theory of Constraints (TOC) theory was developed to find the least efficient areas to increase order throughput and reduce order total cost, but failed to provide a forecast of total production time. Order production varies from order to order due to various customer needs, so the total production time of individual orders can be measured postmortem, but it is difficult to predict in advance. The total measured production time of existing orders is also different, which has limitations that cannot be used as standard time. As a result, experienced managers rely on persimmons rather than on the use of the system, while inexperienced managers use simple management indicators (e.g., 60 days total production time for raw materials, 90 days total production time for steel plates, etc.). Too fast work instructions based on imperfections or indicators cause congestion, which leads to productivity degradation, and too late leads to increased production costs or failure to meet delivery dates due to emergency processing. Failure to meet the deadline will result in compensation for delayed compensation or adversely affect business and collection sectors. In this study, to address these problems, an entity that operates an order production system seeks to find a machine learning model that estimates the total production time of new orders. It uses orders, production, and process performance for materials used for machine learning. We compared and analyzed OLS, GLM Gamma, Extra Trees, and Random Forest algorithms as the best algorithms for estimating total production time and present the results.