Ice-structure interaction (ISI) is a complex process, which requires a thorough understanding of the underlying physics to ensure safe operations in the ice-covered regions. Application of discrete element method (DEM) to compute ice loads on structures is a widely accepted approach, where the equations of rigid body motions are solved for all ice pieces in the computational domain. In most ISI simulations, the ice zone is assumed to be resting on a static water foundation omitting the hydrodynamic effects (added mass, water drag, wave damping) of the interacting bodies. This assumption can introduce erroneous results to simulations of the floating ice floes behavior, which in turn will incur uncertainties in planning ice management activities. In this paper, a smooth particle hydrodynamics (SPH) based computational fluid dynamics (CFD) code is coupled with a three-dimensional DEM model to take the hydrodynamic effects of the interacting bodies including the ice pieces into account. The ice zone is modeled as discrete elements, which allows computing interaction forces by considering contact laws. The water foundation is modeled using smooth particles, which are modelled with the Naiver-Stokes equations. Several applications of ship and offshore structures interacting with level ice and pack ice are simulated. A scenario of an offshore supply vessel operating in the marginal ice zone (MIZ) that is subject to wave forces is also simulated to show how this approach can be used for modelling complex real-world problems. This scenario is unique in a sense that it yields a multi-physics solution, where ice-structure-wave are all included in a single CFD simulation as a fully coupled analysis. The cost of the simulation is significantly reduced by running the computations on a Graphics Processing Unit (GPU) instead of a typical CPU workstation. Some of the initial results of ice-structure interactions are presented in this paper and a reasonable agreement with reduced scale model test results are found.
{"title":"Simulation of Ice-Structure Interactions Using a Coupled SPH-DEM Method","authors":"S. Mintu, D. Molyneux","doi":"10.4043/29139-MS","DOIUrl":"https://doi.org/10.4043/29139-MS","url":null,"abstract":"\u0000 Ice-structure interaction (ISI) is a complex process, which requires a thorough understanding of the underlying physics to ensure safe operations in the ice-covered regions. Application of discrete element method (DEM) to compute ice loads on structures is a widely accepted approach, where the equations of rigid body motions are solved for all ice pieces in the computational domain. In most ISI simulations, the ice zone is assumed to be resting on a static water foundation omitting the hydrodynamic effects (added mass, water drag, wave damping) of the interacting bodies. This assumption can introduce erroneous results to simulations of the floating ice floes behavior, which in turn will incur uncertainties in planning ice management activities.\u0000 In this paper, a smooth particle hydrodynamics (SPH) based computational fluid dynamics (CFD) code is coupled with a three-dimensional DEM model to take the hydrodynamic effects of the interacting bodies including the ice pieces into account. The ice zone is modeled as discrete elements, which allows computing interaction forces by considering contact laws. The water foundation is modeled using smooth particles, which are modelled with the Naiver-Stokes equations.\u0000 Several applications of ship and offshore structures interacting with level ice and pack ice are simulated. A scenario of an offshore supply vessel operating in the marginal ice zone (MIZ) that is subject to wave forces is also simulated to show how this approach can be used for modelling complex real-world problems. This scenario is unique in a sense that it yields a multi-physics solution, where ice-structure-wave are all included in a single CFD simulation as a fully coupled analysis. The cost of the simulation is significantly reduced by running the computations on a Graphics Processing Unit (GPU) instead of a typical CPU workstation. Some of the initial results of ice-structure interactions are presented in this paper and a reasonable agreement with reduced scale model test results are found.","PeriodicalId":422752,"journal":{"name":"Day 1 Mon, November 05, 2018","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115663736","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Seong-Rak Cho, Cheolhee Kim, Eun-Jin Oh, Sungsu Lee
This study describes the ice abrasion test method of commercial coatings for ice-class vessel. The tested specimens are composed of three different coatings: an ice protection coating (IPC), a medium bonding coating (MBC), and an anti-fouling coating (AFC). The abrasion event between ice and coatings was carried out at the ambient temperature of near 0°C, and the surface roughness, and frictional coefficient were measured before and after the abrasion test. In addition, the Ethylene glycol/ Aliphatic detergent (EG/AD) model ice is standard model ice in the KRISO ice model basin and its mechanical properties are similar with the properties of the EG/AD/S model ice was used in this study. The large friction measurement device we used in this study can move up to 2 m, and measures the friction force of the plate over the ice and makes ice abrasion event with model ice. The correlation between the roughness and the coefficient of friction was derived as ice abrasion event progresses. In case of the IPC, the surface roughness increases as the ice abrasion test increases, therefore, a frictional resistance is also bigger and bigger. However, the results for the MBC and the AFC are different because the surface roughnesses were not pretty much changed according to the ice abrasion and the frictional resistances are independent on the ice abrasion. This study can contribute to the development of ice abrasion test method.
{"title":"Study on Ice Abrasion Test Method of Coating Paint for Ice-Class Vessels","authors":"Seong-Rak Cho, Cheolhee Kim, Eun-Jin Oh, Sungsu Lee","doi":"10.4043/29156-MS","DOIUrl":"https://doi.org/10.4043/29156-MS","url":null,"abstract":"\u0000 This study describes the ice abrasion test method of commercial coatings for ice-class vessel. The tested specimens are composed of three different coatings: an ice protection coating (IPC), a medium bonding coating (MBC), and an anti-fouling coating (AFC). The abrasion event between ice and coatings was carried out at the ambient temperature of near 0°C, and the surface roughness, and frictional coefficient were measured before and after the abrasion test. In addition, the Ethylene glycol/ Aliphatic detergent (EG/AD) model ice is standard model ice in the KRISO ice model basin and its mechanical properties are similar with the properties of the EG/AD/S model ice was used in this study. The large friction measurement device we used in this study can move up to 2 m, and measures the friction force of the plate over the ice and makes ice abrasion event with model ice. The correlation between the roughness and the coefficient of friction was derived as ice abrasion event progresses. In case of the IPC, the surface roughness increases as the ice abrasion test increases, therefore, a frictional resistance is also bigger and bigger. However, the results for the MBC and the AFC are different because the surface roughnesses were not pretty much changed according to the ice abrasion and the frictional resistances are independent on the ice abrasion. This study can contribute to the development of ice abrasion test method.","PeriodicalId":422752,"journal":{"name":"Day 1 Mon, November 05, 2018","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121773650","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
While there were certainly marine activities in the approaches to the NW Passages in the pre-Colombian ages, the true search for a passage from the Atlantic to the Pacific, north around Canada was stimulated by the Treat of Tordesillas in 1494, two years after Columbus first "discovered" the Americas. In this treaty, Pope Alexander VI, divided the world beyond Europe between Spain and Portugal, effectively cutting off northern European access to China and the Spice Islands. Almost immediately the King of England funded exploration of alternative routes and in 1497-98, John Cabot made voyages of discovery to the East Coast of N. America and Greenland. He is credited with the discovery of Newfoundland on one of these voyages. Cabot was followed by a long line of others who explored for the NW passage and who have left their names in the geography of the north. Frobisher, Davis, Hudson, Baffin, Franklin, M’Clintock, and M’Clure all attempted to find a sea route from the Atlantic to the Pacific. Further, Drake and Cook centuries apart attempted to find the Pacific end of the Passage without success. The passage was not successfully transited until Amundsen did so over a three-year period completing his transit in 1906, in his ship GJOA, but Larsen in the RCM schooner ST. ROCH made the first true non-stop voyage. Today the idea of using the NW Passage as a commercial route between the Atlantic and the Pacific basins is unattractive, but increasing ship traffic in these waters is being seen with cruise ships, polar research ships, government resupply ships and ships carrying cargo from mining sites in the north. This paper will give some history of the ships that have been used over the last six centuries of exploration for and navigation in the NW Passages, and will suggest that some of the hard-won experiences gained are still relevant today.
虽然在前哥伦比亚时代，在通往西北通道的道路上肯定有海洋活动，但真正寻找从大西洋到太平洋的通道，在加拿大北部，是在1494年，即哥伦布首次“发现”美洲的两年后，Tordesillas的治疗激发了真正的探索。在这个条约中，教皇亚历山大六世将欧洲以外的世界划分给西班牙和葡萄牙，有效地切断了北欧通往中国和香料群岛的通道。几乎立刻，英格兰国王资助了另一条航线的探索。在1497年至1498年，约翰·卡伯特(John Cabot)进行了到北美东海岸和格陵兰岛的发现之旅。人们认为他在其中一次航行中发现了纽芬兰。在卡伯特之后，还有一长串探索西北通道的人，他们在北方的地理上留下了自己的名字。Frobisher, Davis, Hudson, Baffin, Franklin, M 'Clintock和M 'Clure都试图找到一条从大西洋到太平洋的海上航线。此外，几个世纪以来，德雷克和库克试图找到太平洋的尽头，但没有成功。直到1906年，阿蒙森在他的GJOA号船上花了三年时间完成了他的过境，这条通道才成功通过，但拉森在皇家商船公司的圣罗克纵帆船上进行了第一次真正的不间断航行。如今，利用西北航道作为大西洋和太平洋盆地之间的商业航线的想法并不吸引人，但这片水域的船只交通量正在增加，游轮、极地考察船、政府补给船和从北部矿区运送货物的船只都在增加。本文将介绍过去六个世纪以来在西北航道进行探索和航行的船只的一些历史，并将提出一些来之不易的经验，今天仍然相关。
{"title":"The Ships of the Northwest Passages - Six Centuries of Technical & Operational Development","authors":"P. Noble","doi":"10.4043/29095-MS","DOIUrl":"https://doi.org/10.4043/29095-MS","url":null,"abstract":"\u0000 While there were certainly marine activities in the approaches to the NW Passages in the pre-Colombian ages, the true search for a passage from the Atlantic to the Pacific, north around Canada was stimulated by the Treat of Tordesillas in 1494, two years after Columbus first \"discovered\" the Americas. In this treaty, Pope Alexander VI, divided the world beyond Europe between Spain and Portugal, effectively cutting off northern European access to China and the Spice Islands.\u0000 Almost immediately the King of England funded exploration of alternative routes and in 1497-98, John Cabot made voyages of discovery to the East Coast of N. America and Greenland. He is credited with the discovery of Newfoundland on one of these voyages.\u0000 Cabot was followed by a long line of others who explored for the NW passage and who have left their names in the geography of the north. Frobisher, Davis, Hudson, Baffin, Franklin, M’Clintock, and M’Clure all attempted to find a sea route from the Atlantic to the Pacific.\u0000 Further, Drake and Cook centuries apart attempted to find the Pacific end of the Passage without success. The passage was not successfully transited until Amundsen did so over a three-year period completing his transit in 1906, in his ship GJOA, but Larsen in the RCM schooner ST. ROCH made the first true non-stop voyage.\u0000 Today the idea of using the NW Passage as a commercial route between the Atlantic and the Pacific basins is unattractive, but increasing ship traffic in these waters is being seen with cruise ships, polar research ships, government resupply ships and ships carrying cargo from mining sites in the north.\u0000 This paper will give some history of the ships that have been used over the last six centuries of exploration for and navigation in the NW Passages, and will suggest that some of the hard-won experiences gained are still relevant today.","PeriodicalId":422752,"journal":{"name":"Day 1 Mon, November 05, 2018","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125380485","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Remote Sensing Imagery and the derived ancillary products improved the efficiency and safety of upstream oil and gas operations on the North Slope of Alaska. These Arctic regions are remote, very difficult to access in general and sometimes only seasonably accessible. Our prudent and responsible Arctic Operations require regional-reconnaissance exploration, diligent monitoring of environment such as current state of vegetation, temporal changes of terrain, water drainage system and lakes. Finally, we also need very detailed logistical-planning of field operations. Remote sensing imagery and its derived ancillary products demonstrably improved all these aspects of our Arctic Operations. For Arctic Operations, remote sensing data consisted of optical satellite and aerial imagery at various spectral and spatial resolutions, high resolution LIDAR data for digital elevation and digital surface models and synthetic aperture radar imagery (SAR). A combination of in-house and commercial software was used to ingest and process these data. The optical imagery was processed and enhanced using various spectral combinations and high pass filtering to generate the highest possible spatial-resolution for each sensor. Classic neural networks analysis was used to classify the optical imagery for vegetation. The SAR imagery was calibrated (for all polarizations) and geometrically corrected to remove layover effects. The processed optical and SAR imagery, LIDAR and ancillary products were co-registered and imported into a GIS system for final analysis and applications. The optical imagery provided information about surface feature such as lake outlines, general drainage, active channels in Colville River, general lake ice conditions, classification of vegetation types etc. The LIDAR data were used to generate slope maps (for arctic vehicles), general topographic conditions and field operations. The SAR imagery was used to monitor surface conditions when optical imagery was not available during the Arctic night conditions. SAR imagery was also used to calculate the ice thickness proxy maps for eventual field operations. All of these products contributed directly to our environmental baseline studies, improved our field operation efficiency and general safety of our Arctic Operations. For a practicing engineer (individual or team) The remote sensing data and derived products for Arctic Operations were made available via GIS system. This allowed easy integration with other data layers as well as a common background for all different disciplines to monitor progress and to contribute their learnings and ideas to the entire team.
{"title":"Application of Remote Sensing Imagery and Ancillary Products to Improve Safety and Logistical Efficiency of Arctic Operations","authors":"Tiffany C. Carey, K. Soofi","doi":"10.4043/29115-MS","DOIUrl":"https://doi.org/10.4043/29115-MS","url":null,"abstract":"\u0000 Remote Sensing Imagery and the derived ancillary products improved the efficiency and safety of upstream oil and gas operations on the North Slope of Alaska. These Arctic regions are remote, very difficult to access in general and sometimes only seasonably accessible. Our prudent and responsible Arctic Operations require regional-reconnaissance exploration, diligent monitoring of environment such as current state of vegetation, temporal changes of terrain, water drainage system and lakes. Finally, we also need very detailed logistical-planning of field operations. Remote sensing imagery and its derived ancillary products demonstrably improved all these aspects of our Arctic Operations.\u0000 For Arctic Operations, remote sensing data consisted of optical satellite and aerial imagery at various spectral and spatial resolutions, high resolution LIDAR data for digital elevation and digital surface models and synthetic aperture radar imagery (SAR). A combination of in-house and commercial software was used to ingest and process these data. The optical imagery was processed and enhanced using various spectral combinations and high pass filtering to generate the highest possible spatial-resolution for each sensor. Classic neural networks analysis was used to classify the optical imagery for vegetation. The SAR imagery was calibrated (for all polarizations) and geometrically corrected to remove layover effects. The processed optical and SAR imagery, LIDAR and ancillary products were co-registered and imported into a GIS system for final analysis and applications.\u0000 The optical imagery provided information about surface feature such as lake outlines, general drainage, active channels in Colville River, general lake ice conditions, classification of vegetation types etc. The LIDAR data were used to generate slope maps (for arctic vehicles), general topographic conditions and field operations. The SAR imagery was used to monitor surface conditions when optical imagery was not available during the Arctic night conditions. SAR imagery was also used to calculate the ice thickness proxy maps for eventual field operations. All of these products contributed directly to our environmental baseline studies, improved our field operation efficiency and general safety of our Arctic Operations.\u0000 For a practicing engineer (individual or team) The remote sensing data and derived products for Arctic Operations were made available via GIS system. This allowed easy integration with other data layers as well as a common background for all different disciplines to monitor progress and to contribute their learnings and ideas to the entire team.","PeriodicalId":422752,"journal":{"name":"Day 1 Mon, November 05, 2018","volume":"418 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116685921","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
D. Power, C. Howell, K. Dodge, F. Scibilia, J. R. Sagli, R. Hall
Drifting icebergs can threaten navigation and marine operations and are prevalent in a number of regions that have active oil and gas exploration and development. Satellite synthetic aperture radar (SAR) is naturally applicable to map and monitor icebergs and sea ice due its ability to capture images day or night, as well as through cloud, fog and various wind conditions. There are several notable examples of its use to support operations, including Grand Banks, Barents Sea, offshore Greenland and Kara Sea. New constellations of satellites and the increasing volume of satellite data becoming available present a new paradigm for ice surveillance, in terms of persistence, reliability and cost. To fully extract the value of the data from these constellations, automation and cloud-based processing must be implemented. This will allow more timely and efficient processing, lowering monitoring costs by at least an order of magnitude. The increase in data persistence and processing capability allows large regions to be monitored daily for ice incursions, thus increasing safety and efficiency during offshore operations in those regions. The process of automating SAR-based iceberg surveillance involves creating a process flow that is robust and requires limited human intervention. The process flow involves land-masking, target detection, target discrimination and product dissemination. Land masking involves the removal of high-clutter land from the imagery to eliminate false detection from these locations. Target detection usually involves an adaptive threshold to separate true targets from the background ocean clutter. A constant false alarm rate (CFAR) is a standard technique used in radar image processing for this purpose. Target discrimination involves an examination of the distinct features of a target to determine if they match the features of icebergs, vessels or other ‘false alarms’ (e.g., marine wildlife, clutter). The final stage is the production of an output surveillance product, which can be a standard iceberg chart (e.g., MANICE) or something that can be ingested into a GIS system (e.g., ESRI shapefile, Google KML). The target discrimination phase is one of the most important phases because it provides feedback to operations about the presence of targets of interest (icebergs and vessels). The authors have used computer vision techniques successfully to train target classifiers. Standard techniques usually result in classifier accuracies of between 85%-95%, depending on the resolution of the SAR (higher resolutions produce more accurate results) and the availability of multiple polarizations. To see if new machine learning techniques could be applied to increase classifier accuracy, a dataset of 5000 ship and iceberg targets were extracted from Sentinel-1 multi-channel data (HH,HV). The images were collected in several regions (Greenland, Grand Banks, and Strait of Gibraltar). Validation either came by way of supporting information from
漂浮的冰山可能会威胁到航行和海上作业，并且在一些活跃的石油和天然气勘探和开发地区普遍存在。卫星合成孔径雷达(SAR)由于能够在白天或夜间，以及在云、雾和各种风条件下捕获图像，因此自然适用于绘制和监测冰山和海冰。有几个值得注意的例子使用它来支持作业，包括大浅滩、巴伦支海、格陵兰近海和喀拉海。在持久性、可靠性和成本方面，新的卫星星座和日益增加的可用卫星数据量为冰监测提供了一种新的范例。为了从这些星座中充分提取数据的价值，必须实施自动化和基于云的处理。这将使处理更加及时和有效，将监测成本至少降低一个数量级。数据持久性和处理能力的提高使得每天可以监测大区域的冰侵情况，从而提高这些区域海上作业的安全性和效率。基于sar的冰山监测自动化过程涉及创建一个健壮的流程，并且需要有限的人为干预。过程流程包括陆地掩蔽、目标检测、目标识别和产品传播。土地掩蔽包括从图像中去除高杂波土地，以消除这些位置的错误检测。目标检测通常涉及自适应阈值，以从背景海洋杂波中分离真实目标。恒定虚警率(CFAR)是一种用于雷达图像处理的标准技术。目标识别包括检查目标的不同特征，以确定它们是否与冰山、船只或其他“假警报”(例如，海洋野生动物、杂波)的特征相匹配。最后一个阶段是输出监控产品的生产，它可以是一个标准的冰山图(例如，MANICE)或可以被吸收到GIS系统中的东西(例如，ESRI shapefile, Google KML)。目标识别阶段是最重要的阶段之一，因为它向作战提供有关感兴趣目标(冰山和船只)存在的反馈。作者已经成功地使用计算机视觉技术来训练目标分类器。标准技术通常导致分类器准确率在85%-95%之间，这取决于SAR的分辨率(更高的分辨率产生更准确的结果)和多极化的可用性。为了了解是否可以应用新的机器学习技术来提高分类器的精度，从Sentinel-1多通道数据(HH,HV)中提取了5000艘船舶和冰山目标的数据集。这些图像是在几个地区(格陵兰岛、大浅滩和直布罗陀海峡)收集的。验证要么来自海上作业的支持信息，要么来自地点的推断。Kaggle公司举办了一场在线机器学习竞赛，这是一家代表客户举办在线竞赛的公司。检测数据由Kaggle提供给广泛的互联网社区。Kaggle有一群忠实的数据科学家，他们经常参加Kaggle的比赛。比赛举办了三个月;超过3300支队伍参加了比赛。比赛产生了一种优于标准计算机视觉技术的分类器;前三名竞争者有4-5个阶段分类器，将分类精度提高了大约5%。
{"title":"Towards Automation of Satellite-Based Radar Imagery for Iceberg Surveillance - Machine Learning of Ship and Iceberg Discrimination","authors":"D. Power, C. Howell, K. Dodge, F. Scibilia, J. R. Sagli, R. Hall","doi":"10.4043/29130-MS","DOIUrl":"https://doi.org/10.4043/29130-MS","url":null,"abstract":"\u0000 Drifting icebergs can threaten navigation and marine operations and are prevalent in a number of regions that have active oil and gas exploration and development. Satellite synthetic aperture radar (SAR) is naturally applicable to map and monitor icebergs and sea ice due its ability to capture images day or night, as well as through cloud, fog and various wind conditions. There are several notable examples of its use to support operations, including Grand Banks, Barents Sea, offshore Greenland and Kara Sea.\u0000 New constellations of satellites and the increasing volume of satellite data becoming available present a new paradigm for ice surveillance, in terms of persistence, reliability and cost. To fully extract the value of the data from these constellations, automation and cloud-based processing must be implemented. This will allow more timely and efficient processing, lowering monitoring costs by at least an order of magnitude. The increase in data persistence and processing capability allows large regions to be monitored daily for ice incursions, thus increasing safety and efficiency during offshore operations in those regions.\u0000 The process of automating SAR-based iceberg surveillance involves creating a process flow that is robust and requires limited human intervention. The process flow involves land-masking, target detection, target discrimination and product dissemination. Land masking involves the removal of high-clutter land from the imagery to eliminate false detection from these locations. Target detection usually involves an adaptive threshold to separate true targets from the background ocean clutter. A constant false alarm rate (CFAR) is a standard technique used in radar image processing for this purpose. Target discrimination involves an examination of the distinct features of a target to determine if they match the features of icebergs, vessels or other ‘false alarms’ (e.g., marine wildlife, clutter). The final stage is the production of an output surveillance product, which can be a standard iceberg chart (e.g., MANICE) or something that can be ingested into a GIS system (e.g., ESRI shapefile, Google KML).\u0000 The target discrimination phase is one of the most important phases because it provides feedback to operations about the presence of targets of interest (icebergs and vessels). The authors have used computer vision techniques successfully to train target classifiers. Standard techniques usually result in classifier accuracies of between 85%-95%, depending on the resolution of the SAR (higher resolutions produce more accurate results) and the availability of multiple polarizations. To see if new machine learning techniques could be applied to increase classifier accuracy, a dataset of 5000 ship and iceberg targets were extracted from Sentinel-1 multi-channel data (HH,HV). The images were collected in several regions (Greenland, Grand Banks, and Strait of Gibraltar). Validation either came by way of supporting information from ","PeriodicalId":422752,"journal":{"name":"Day 1 Mon, November 05, 2018","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115777398","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The benefits of using satellite imagery in arctic maritime operations are well known. Synthetic Aperture Radar and optical imagery from polar orbiting satellites can provide valuable information about sea ice and presence of icebergs both on a local and regional scale. The sea ice information extracted from satellite imagery is used together with weather data for vessel navigation in or near the ice or for increased safety and reduced risk during critical operations. Kongsberg Satellite Services (KSAT) has ordering, downlink and processing capabilities for all the commercial and free SAR satellites in orbit today. SAR satellite imagery from these sources can, in addition to be used for detection and monitoring of sea ice, also be used for large scale environmental monitoring (oil spill detection) and increased maritime domain awareness (vessel detection). StormGeo is a leading weather risk provider for operations in Arctic, and has a strong focus on delivering weather decision support to marine operations. For the end-user performing ice analysis, satellite imagery can be used in addition to information such as local weather forecasts and ice information extracted from external sources. For efficient ordering of satellite imagery in ice management operations, it is important that the end-user have access to satellite tasking information such as potential temporal and spatial coverage, tasking deadlines and order status. In addition, the end-user must be able to access the relevant data as fast as possible after satellite acquisition. KSAT and StormGeo have in cooperation with Viking Supply Ships developed an end-to-end service integrating relevant ice-information and interfaces for satellite ordering, imagery access and weather information. The service is accessed through the StormGeo GUI, "Vortex," which serves as a robust and powerful tool for information access and ice management analysis. The service development has been done in the MULDIARCOS (Multi-mission Data and Information Services for Arctic Operations) project, which has been partly funded by ESA under the Integrated Application Promotion program.
{"title":"Integration of Multi-Mission Satellite Data, Weather and Ice Information for Arctic Operations","authors":"Andreas Hay Kaljord, Svein Inge Andersen","doi":"10.4043/29153-ms","DOIUrl":"https://doi.org/10.4043/29153-ms","url":null,"abstract":"\u0000 The benefits of using satellite imagery in arctic maritime operations are well known. Synthetic Aperture Radar and optical imagery from polar orbiting satellites can provide valuable information about sea ice and presence of icebergs both on a local and regional scale. The sea ice information extracted from satellite imagery is used together with weather data for vessel navigation in or near the ice or for increased safety and reduced risk during critical operations.\u0000 Kongsberg Satellite Services (KSAT) has ordering, downlink and processing capabilities for all the commercial and free SAR satellites in orbit today. SAR satellite imagery from these sources can, in addition to be used for detection and monitoring of sea ice, also be used for large scale environmental monitoring (oil spill detection) and increased maritime domain awareness (vessel detection). StormGeo is a leading weather risk provider for operations in Arctic, and has a strong focus on delivering weather decision support to marine operations.\u0000 For the end-user performing ice analysis, satellite imagery can be used in addition to information such as local weather forecasts and ice information extracted from external sources. For efficient ordering of satellite imagery in ice management operations, it is important that the end-user have access to satellite tasking information such as potential temporal and spatial coverage, tasking deadlines and order status. In addition, the end-user must be able to access the relevant data as fast as possible after satellite acquisition.\u0000 KSAT and StormGeo have in cooperation with Viking Supply Ships developed an end-to-end service integrating relevant ice-information and interfaces for satellite ordering, imagery access and weather information. The service is accessed through the StormGeo GUI, \"Vortex,\" which serves as a robust and powerful tool for information access and ice management analysis.\u0000 The service development has been done in the MULDIARCOS (Multi-mission Data and Information Services for Arctic Operations) project, which has been partly funded by ESA under the Integrated Application Promotion program.","PeriodicalId":422752,"journal":{"name":"Day 1 Mon, November 05, 2018","volume":"16 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125236809","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The paper describes a simulation tool for simulating the transit of ships through brash ice channels, based on the Discrete Element Method (DEM). Fundamentals of the method are given, including contact detection and forces calculation. Artificial brash ice channels are created in the simulation domain by the so-called floating-up technique. Hull geometry is introduced into the model, handling non-convex bodies as composites of convex bodies. Hydrostatic properties are calculated according to the actual draft, pitch, and roll angles. In order to calibrate the parameters of the code, a standard cylinder experiment is simulated and the results are compared with the experimental model test results. Graphical output of the simulation is also compared with underwater camera footage. General behavior of the ice particles is identical in the vicinity of the structure. However, ice loads on the structure exhibit some discrepancies. Simulation of an Ice Class Tanker was also carried out, and the results were compared with experimental model test values and under water videos. In this case, ice loads tend to be higher than expected. However, particle behavior near hull is very satisfactory. The cause for high ice loads is identified to be deficiencies in modelling the behavior of far field ice particles in the current tool. The simulation tends to overestimate the particle motions in far field due to the deficiencies in the implemented friction model (Cundall-Strack Friction). The current tool is suitable for obtaining qualitative results on ships navigating in brash ice channel in the early design stage; especially to visualize the ice particle flow around ship hull and identify possible concentration of ice particles especially around appendages.
{"title":"Discrete Element Simulation of Ships Navigating Through Brash Ice Channels","authors":"M. Prasanna, Q. Hisette","doi":"10.4043/29163-MS","DOIUrl":"https://doi.org/10.4043/29163-MS","url":null,"abstract":"\u0000 The paper describes a simulation tool for simulating the transit of ships through brash ice channels, based on the Discrete Element Method (DEM). Fundamentals of the method are given, including contact detection and forces calculation. Artificial brash ice channels are created in the simulation domain by the so-called floating-up technique. Hull geometry is introduced into the model, handling non-convex bodies as composites of convex bodies. Hydrostatic properties are calculated according to the actual draft, pitch, and roll angles. In order to calibrate the parameters of the code, a standard cylinder experiment is simulated and the results are compared with the experimental model test results. Graphical output of the simulation is also compared with underwater camera footage. General behavior of the ice particles is identical in the vicinity of the structure. However, ice loads on the structure exhibit some discrepancies. Simulation of an Ice Class Tanker was also carried out, and the results were compared with experimental model test values and under water videos. In this case, ice loads tend to be higher than expected. However, particle behavior near hull is very satisfactory. The cause for high ice loads is identified to be deficiencies in modelling the behavior of far field ice particles in the current tool. The simulation tends to overestimate the particle motions in far field due to the deficiencies in the implemented friction model (Cundall-Strack Friction). The current tool is suitable for obtaining qualitative results on ships navigating in brash ice channel in the early design stage; especially to visualize the ice particle flow around ship hull and identify possible concentration of ice particles especially around appendages.","PeriodicalId":422752,"journal":{"name":"Day 1 Mon, November 05, 2018","volume":"73 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125967076","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
The thickened width of floating ice roads has tended to be a practical consideration rather than a design aspect. Standard methods of calculating the required thickness of ice roads consider the road to be of infinite length and width. In this paper we outline calculations of the bending stress for a finite width ice road. The recommended minimum width that should be thickened to the design value is given below where Lc is the ice characteristic length: Longitudinal wet cracks reduce the load bearing capacity of an ice road. Stress analysis indicated that as long as the ice is less than 1.83m thick and the footprint of the vehicle is longer than 10 m (33 ft) then a safe and simple to use estimate of the road capacity for a vehicle travelling parallel and adjacent to the crack is given by:
{"title":"The Design Width of Floating Ice Roads and Effect of Longitudinal Cracks","authors":"P. Spencer, Ruixue Wang","doi":"10.4043/29164-ms","DOIUrl":"https://doi.org/10.4043/29164-ms","url":null,"abstract":"\u0000 The thickened width of floating ice roads has tended to be a practical consideration rather than a design aspect. Standard methods of calculating the required thickness of ice roads consider the road to be of infinite length and width. In this paper we outline calculations of the bending stress for a finite width ice road. The recommended minimum width that should be thickened to the design value is given below where Lc is the ice characteristic length:\u0000 Longitudinal wet cracks reduce the load bearing capacity of an ice road. Stress analysis indicated that as long as the ice is less than 1.83m thick and the footprint of the vehicle is longer than 10 m (33 ft) then a safe and simple to use estimate of the road capacity for a vehicle travelling parallel and adjacent to the crack is given by:","PeriodicalId":422752,"journal":{"name":"Day 1 Mon, November 05, 2018","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134053174","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
P. Kountouris, L. Rabenstein, P. Cochrane, T. Krumpen, S. Hendricks
Today's ice information is already outdated the moment it is available, due to sea-ice drift. All Arctic stakeholders are in an urgent need for ice forecasts. Presently there is no high-resolution ice forecast product available on the market. PRIIMA is going to tackle this problem. PRIIMA is being developed in a 6 months kick-start project funded by the European Space Agency (ESA). It started on March 1, 2018. PRIIMA combines the lower resolution forecast information from operational sea-ice and weather models with an actual satellite image of the ice cover. It performs an image transformation from the recorded satellite image to a predicted image how it might look in 1-3 days. The process involves translation and rotation of ice features as well as scaling of the ice area. The concept is pragmatic in the sense that it establishes a helpful product developed in close collaboration with our test users from the field of cargo shipping, research ice breakers and expedition cruises. The prediction of sea-ice situations by image warping of near-real time radar images can be differentiated into scenarios with increasing complexity: Free drifting ice away from the coast with a relatively homogenous wind field can be addressed with a single global transformation operator (G1-method) or determined on the bases of the four corner coordinates of the image (L4C-method).Ice drift close to the coast or in presence of heterogeneous wind fields requires local transformation of subsets of the SAR image. A possible solution is to define a dense grid of control points which will constrain the movement of the inland pixels(LMP method). The quality of PRIIMA primarily depends on the accuracy of the available wind forecasts. In free drifting sea-ice a 24-hours forecast of the position of individual ice features was within 1 km to the true position. PRIIMA delivers ice forecasts with the resolution of a satellite radar image. It enables the operating ice manager a quick assessment of the upcoming ice situation.
{"title":"Predicted Ice Images PRIIMA: Methodology and System Evaluation","authors":"P. Kountouris, L. Rabenstein, P. Cochrane, T. Krumpen, S. Hendricks","doi":"10.4043/29127-MS","DOIUrl":"https://doi.org/10.4043/29127-MS","url":null,"abstract":"\u0000 \u0000 \u0000 Today's ice information is already outdated the moment it is available, due to sea-ice drift. All Arctic stakeholders are in an urgent need for ice forecasts. Presently there is no high-resolution ice forecast product available on the market. PRIIMA is going to tackle this problem. PRIIMA is being developed in a 6 months kick-start project funded by the European Space Agency (ESA). It started on March 1, 2018.\u0000 \u0000 \u0000 \u0000 PRIIMA combines the lower resolution forecast information from operational sea-ice and weather models with an actual satellite image of the ice cover. It performs an image transformation from the recorded satellite image to a predicted image how it might look in 1-3 days. The process involves translation and rotation of ice features as well as scaling of the ice area. The concept is pragmatic in the sense that it establishes a helpful product developed in close collaboration with our test users from the field of cargo shipping, research ice breakers and expedition cruises.\u0000 \u0000 \u0000 \u0000 The prediction of sea-ice situations by image warping of near-real time radar images can be differentiated into scenarios with increasing complexity: Free drifting ice away from the coast with a relatively homogenous wind field can be addressed with a single global transformation operator (G1-method) or determined on the bases of the four corner coordinates of the image (L4C-method).Ice drift close to the coast or in presence of heterogeneous wind fields requires local transformation of subsets of the SAR image. A possible solution is to define a dense grid of control points which will constrain the movement of the inland pixels(LMP method).\u0000 The quality of PRIIMA primarily depends on the accuracy of the available wind forecasts. In free drifting sea-ice a 24-hours forecast of the position of individual ice features was within 1 km to the true position.\u0000 \u0000 \u0000 \u0000 PRIIMA delivers ice forecasts with the resolution of a satellite radar image. It enables the operating ice manager a quick assessment of the upcoming ice situation.\u0000","PeriodicalId":422752,"journal":{"name":"Day 1 Mon, November 05, 2018","volume":"61 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129582696","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Due to their potential instabilities, deploying personnel onto icebergs to make direct in-situ measurement is hazardous. The preliminary results from an investigation into the usage of Unmanned Aerial Vehicles (UAV) for surveying and monitoring icebergs are presented. The project had four objectives: (i) acquisition of imagery for the generation of iceberg topside reconstructions using photogrammetry; (ii) development of a GPS tracking device and a deployment mechanism to place it onto an iceberg; (iii) development of a motion sensor to record the motion of an iceberg and a deployment mechanism to deliver it onto an iceberg; and (iv) iceberg draft measurements from a UAV-mounted ice penetrating radar. The project has used both commercially available and custom-built UAVs. The sensor packages (cameras, tracking devices, accelerometers and ground penetrating radar) were commercial products that have been modified for this study and, when required, mountings and delivery mechanisms have been designed and manufactured to integrate the system together. Fieldwork was performed during the 2017 iceberg season in a near-shore environment (Bonavista, Newfoundland and Labrador, Canada) aboard a survey vessel and, in 2018, from an operational supply vessel offshore Newfoundland and Labrador. The field campaigns were conducted in parallel with an iceberg profiling system that uses an integrated multibeam sonar and LiDAR system to generate composite (topside and subsurface) iceberg reconstructions. These reconstructions can be compared with the results obtained from the photogrammetry and the radar survey. During the 2017 program, iceberg imagery for photogrammetry was acquired and GPS tracking devices were deployed onto icebergs and sea-ice. The longest iceberg track obtained was 21 days. For the 2018 campaign, further photogrammetric data was collected and ground penetrating radar surveys of icebergs were performed. The photogrammetry topside reconstructions and the draft estimates from the ground penetrating radar produced results comparable to measurements from the iceberg profiling system. This project has explored the capability of UAVs to deliver sensor packages onto icebergs, and to take aerial measurements over and around them. They are an emerging technology that, although challenging to work with in the harsh North Atlantic environment, have proved useful.
{"title":"Usage of Unmanned Aerial Vehicles for Iceberg Surveying and Monitoring - Preliminary Results","authors":"R. Briggs, Carl Thibault, L. Mingo","doi":"10.4043/29132-MS","DOIUrl":"https://doi.org/10.4043/29132-MS","url":null,"abstract":"\u0000 Due to their potential instabilities, deploying personnel onto icebergs to make direct in-situ measurement is hazardous. The preliminary results from an investigation into the usage of Unmanned Aerial Vehicles (UAV) for surveying and monitoring icebergs are presented. The project had four objectives: (i) acquisition of imagery for the generation of iceberg topside reconstructions using photogrammetry; (ii) development of a GPS tracking device and a deployment mechanism to place it onto an iceberg; (iii) development of a motion sensor to record the motion of an iceberg and a deployment mechanism to deliver it onto an iceberg; and (iv) iceberg draft measurements from a UAV-mounted ice penetrating radar.\u0000 The project has used both commercially available and custom-built UAVs. The sensor packages (cameras, tracking devices, accelerometers and ground penetrating radar) were commercial products that have been modified for this study and, when required, mountings and delivery mechanisms have been designed and manufactured to integrate the system together.\u0000 Fieldwork was performed during the 2017 iceberg season in a near-shore environment (Bonavista, Newfoundland and Labrador, Canada) aboard a survey vessel and, in 2018, from an operational supply vessel offshore Newfoundland and Labrador. The field campaigns were conducted in parallel with an iceberg profiling system that uses an integrated multibeam sonar and LiDAR system to generate composite (topside and subsurface) iceberg reconstructions. These reconstructions can be compared with the results obtained from the photogrammetry and the radar survey.\u0000 During the 2017 program, iceberg imagery for photogrammetry was acquired and GPS tracking devices were deployed onto icebergs and sea-ice. The longest iceberg track obtained was 21 days. For the 2018 campaign, further photogrammetric data was collected and ground penetrating radar surveys of icebergs were performed. The photogrammetry topside reconstructions and the draft estimates from the ground penetrating radar produced results comparable to measurements from the iceberg profiling system.\u0000 This project has explored the capability of UAVs to deliver sensor packages onto icebergs, and to take aerial measurements over and around them. They are an emerging technology that, although challenging to work with in the harsh North Atlantic environment, have proved useful.","PeriodicalId":422752,"journal":{"name":"Day 1 Mon, November 05, 2018","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134574293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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