• Journal of Ocean Engineering and Technology
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• v.11 no.3
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• pp.144-152
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• 1997

본 논문에서는 1년생 빙맥에 의하여 해양구조물에 작용하는 하중을 추정할 수 있는 모델을 제시하였다. 1년생 빙맥을 수면하부(keel), 수면상부(sail), 경화층(consolidated layer)의 3부분으로 나누어 각 부분에 의한 하중을 추정할 수 있는 방법을 논의하였다. 수면하부는 얼음조각(ice rubble)이 층으로 쌓여져 형성된 것이므로 수면하부에 의한 하중추정을 할 때 얼음조각을 선형 Mohr-Coulomb재료로 생각하여 토질역학(soil mechanics)의 이론을 사용하였다. 수면상부에 의한 하중도 토질역학 이론을 이용하여 추정하였으며 경화층에 의한 하중은 Korzhavin식을 이용하여 추정하였다. 제시한 모델을 이용하여 빙맥하중 추정에 미치는 인자들의 영향을 검토하였다.

• Journal of Ocean Engineering and Technology
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• v.16 no.1
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• pp.27-35
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• 2002

The interaction of grounded ice ridges with underlying seabed is one of the major considerations in the design of Arctic pipeline system. Previously several ice scour models were developed by researchers to describe the ice scour-seabed interaction mechanism. In view of possible improvements, a comparative study of those ice scour models is performed and their limitation in modeling is discussed. Simple laboratory tests are carried out and then the shape pattern of deposited soil around the ice model is newly defined. Unlike the rectangular idealization of an ice block, in this modified ice scour model, trapezoidal cross sections are assumed to represent the typical shape of an ice ridge based on the field observation data. With the horizontal and vertical motion of ice model, the ice scour depth and soil reacting forces on seabed are calculated with varying the keel angle of an ice ridge.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2018.11a
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• pp.175-176
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• 2018

여름철 북극 해빙 면적의 감소 추세로 빙해선박의 북극항로 통항회수가 증가하고 있어 선박의 안전 항해를 위한 기술 개발에 관심이 집중되고 있다. 본 연구에서는 선박해양플랜트연구소에서 개발 중인 KRISO Arctic Safe Routing System(KARS)의 개념과 함께 핵심 모듈 중 하나인 빙저항 추진 성능 DB 개발 과정을 소개하였다. 우선 빙해수조에서 다양한 빙상환경(평탄빙, 유빙, 빙맥 등)에 따른 선박의 빙성능 평가 시험을 수행한 후 대상선박의 기본적인 빙성능을 도출하였고 빙성능 추정 S/W의 해석결과와 비교 검증을 수행하여 다양한 환경 변수를 고려한 빙저항 추진 성능 DB를 생성하였다. 아울러, 생성된 DB의 검증을 위해 2017년 8월 쇄빙연구선 아라온의 빙해역 실선시험 동안 계측된 결과와 비교 분석하여 정확도를 분석하였고 KARS의 개선 사항 및 향후 활용 가능성을 고찰하였다.

• Journal of the Korean Society of Mechanical Technology
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• v.13 no.4
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• pp.109-115
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• 2011

The ice tank is important facility to check the performance of the ship and offshore in ice condition before the construction. MOERI(Maritime & Ocean Engineering Research Institute) constructed ice model basin on the end of 2010. The ice technology to know the phenomena of ice near the ship and to estimate power of the ship in model scale is the main characteristic of the ice model basin. To achieve this goal in one ice sheet, making of test plan and feasibility check of test possibility have to review in the beginning stage of the every test. This paper describes the number of maximum resistance and self propulsion test in a sheet of level ice and proposes the methodology to optimize pack ice, rubble ice, brash ice and ice ridge test in MOERI ice tank. The feasibility of free running test to know maneuvering performance in ice field and some specific idea to measuring ice thickness and ice ridge shape was proposed.

• Korean Journal of Remote Sensing
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• v.23 no.6
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• pp.507-520
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• 2007

Satellite passive microwave(PM) sensors have been observing polar sea ice concentration(SIC), ice temperature, and snow depth since 1970s. Among them SIC is playing an important role in the various studies as it is considered the first factor for the monitoring of global climate and environment changes. Verification and correction of PM SIC is essential for this purpose. In this study, we calculated SIC from KOMPSAT-1 EOC images obtained from Arctic sea ice edges from July to August 2005 and compared with SSM/I SIC calculated from NASA Team(NT) algorithm. When we have no consideration of sea ice types, EOC and SSM/I NT SIC showed low correlation coefficient of 0.574. This is because there are differences in spatial resolution and observing time between two sensors, and the temporal and spatial variation of sea ice was high in summer Arctic ice edge. For the verification of SSM/I NT SIC according to sea ice types, we divided sea ice into land-fast ice, pack ice, and drift ice from EOC images, and compared them with SSM/I NT SIC corresponding to each ice type. The concentration of land-fast ice between EOC and SSM/I SIC were calculated very similarly to each other with the mean difference of 0.38%. This is because the temporal and spatial variation of land-fast ice is small, and the snow condition on the ice surface is relatively dry. In case of pack ice, there were lots of ice ridge and new ice that are known to be underestimated by NT algorithm. SSM/I NT SIC were lower than EOC SIC by 19.63% in average. In drift ice, SSM/I NT SIC showed 20.17% higher than EOC SIC in average. The sea ice with high concentration could be included inside the wide IFOV of SSM/I because the drift ice was located near the edge of pack ice. It is also suggested that SSM/I NT SIC overestimated the drift ice covered by wet snow.