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When designing subsea pipelines, flowlines or cables to traverse shallow offshore regions with icebergs, iceberg keel interactions may be of concern. Given sufficiently low contact rates, the possibility of laying the pipe or cable on the seabed without burial may be an option. Consideration is then needed regarding possible denting, buckling, or lateral forces which can result in high axial tensions. In previous analyses of keel interactions, the ice keels have been treated as rigid, under the assumption that the ice strength is significantly higher than the soil strength. Recent studies have shown that under rapid loading, soil resistance can be significantly higher than previously considered, while conservatisms in estimates of ice strength have been reduced over time. As a result, ice-pipe-soil interactions are being reassessed as part of a study "SIIBED: Subsea Ice Interaction Barriers to Energy Development" (Ralph et al., 2023). This paper discusses background and progress on one component of that study, the development of improved ice strength inputs for an overall ice-pipe-soil finite element model (Barrett et al., 2023). The paper includes a review of relevant literature and describes the use of different finite-element (FEA) techniques to better understand relevant ice failure processes. Calibration of the models is largely based on the results of a medium-scale test program using a novel test frame, RHITA (Rapid-High-capacity-Impact-Testing-Apparatus), which was designed and built especially for the project.

Medium scale indentation tests have been conducted using a 12.75" diameter rigid pipe indenter, mounted on a purposely designed test frame (RHITA – Rapid High-capacity Impact Test Apparatus) and large laboratory made freshwater ice samples (approximately 4 m3 each). The purpose of this study is to collect ice failure data, representative of iceberg keel interactions with subsea pipelines or electrical cables laying on the seabed. Previous assessments of pipe response due to iceberg impact conservatively assumed no ice failure. As no widely accepted numerical models is available that captures prevalent ice failure mechanisms, experimental data was collected using RHITA. The data can be implemented in a coupled ice-pipe-soil FEA as a pressure or force limit to the ice. Also, the data can serve for calibration and validation of numerical models of ice fracture or ice crushing. The tests were executed at 0.2 m/s, a typical iceberg drift speed, on the Grand Banks of Newfoundland and Labrador. An ice mould was used to grow ice samples measuring 2.5x1.5x1.0 m (LxWxH). The top half of the ice sample was exposed, the bottom half confined by the mould. Global loads during the 2.0 m interaction were measured using six load cells, and tactile pressure sensors were used to measure the ice pressure distribution on the indenter. The test matrix includes variations of interaction depth, ice geometry, embedded rock material and ice temperature. The observed ice failure mechanisms ranged from localized damage near the interaction zone, to large fractures spanning the entire sample. The tactile pressure sensors showed the interface pressure distribution across the contact area, largely affected by local spalling events. Ice temperature and associated boundary conditions were found to affect the propagation of the cracks and resulting loads. This paper presents a summary of the tests executed from June 2022 to January 2023. Future works will include testing of rigid and flexible flowlines, and subsea electrical cable samples.

While society benefits from Arctic shipping, it is necessary to recognize that ship operations in Arctic waters pose significant risks to people, the environment, and property. To support the management of those risks, this article presents a comprehensive approach addressing both short-term operational risks, as well as risks related to long-term extreme ice loads. For the management of short-term operational risks, an extended version of the Polar Operational Limit Assessment Risk Indexing System (POLARIS) considering the magnitude of the consequences of potential adverse events is proposed. For the management of risks related to long-term extreme ice loads, guidelines are provided for using existing analytical, numerical, and semi-empirical methods. In addition, to support the design of ice class ship structures, the article proposes a novel approach that can be used in the conceptual design phase for the determination of preliminary scantlings for primary hull structural members.

Risk aggregation is the process of combining multiple individual risks to develop a better understanding of the overall risk on a system. Different risks can have different consequences and different units of measure. This study contributes to the process of risk aggregation by presenting a general method to combine multiple consequences posed by an Arctic ship accident. The method considers ecological and socio-economic consequences of a potential oil spill, and life-safety consequences of a potential ship evacuation. Existing models for each consequence type are adopted. Individual consequence types are monetized and combined to quantify total consequence cost for a given accident scenario. A framework is proposed to assign a qualitative rating for total consequence severity. The qualitative scales of the framework are established using the quantitative method. Total consequence severity is evaluated for different ship types and regions in the Canadian Arctic. Results indicate that Arctic ship accidents involving oil tankers in environmentally sensitive regions and cruise ships in regions associated with long response times are worst-case scenarios, with similar total consequence severity levels. Implications for safe Arctic shipping are that on the basis of total consequence severity, mitigating the potential consequence severity of Arctic cruise operations is of near equal priority to that of Arctic tanker operations. Evaluating total consequence severity of potential Arctic ship accidents provides decision-makers and risk analysts with a data-driven tool to integrate multidisciplinary knowledge for the assessment, management, and communication of Arctic shipping risks.

Visual data is abundantly available and provides rich information about real-world objects. Computer vision is a substantial and growing field, which seeks to distill useful information from photographic imagery. The primary focus of this work centers on the application of machine learning based computer vision algorithms in order to produce characterizations of the visible sea ice conditions. The specific task approached herein is known as semantic segmentation; the methodology by which each region of an image, at an individual pixel level, is assigned a classification from a predetermined set of possible classes., SNAME Maritime Convention 2022, september 26-29, 2022, Houston, Texas, US

Arctic shipping is growing driven by a demand for natural resources, climate change, and technological development, among other factors. While this provides many benefits for society, it also entails risks for people, the environment, and property. The purpose of this article is to assist ship designers, operators, owners, and other stakeholders in managing those risks by defining a comprehensive approach to scenario-based risk management for Arctic waters. The approach covers both the management of short-term operational risks, as well as of risks related to a ship’s long-term extreme (design) ice loads and structural response. For operational risk management, a further developed version of the established Polar Operational Limitations Assessment Risk Indexing System (POLARIS) method is defined. In contrast to the established method, the further developed version considers the consequences of potential accidental events. For managing risks related to a ship’s long-term extreme ice loads and structural response, guidelines are provided for the application of existing methods of assessing ice loads, including analytical, numerical, and semi-empirical methods. In addition, to support the design of ice class ship structures, a new approach based on closed-form expressions is defined that can be used in the conceptual design phase to determine preliminary scantlings of primary hull structural members (e.g., transverse web frames).

Supply vessels for the Grand Banks oil and gas industry have faced 25 ice blockage events entering St. John’s Harbour, Newfoundland from 1979-2005. We propose an empirical approach to forecasting the occurrence of 8-10/10ths total ice concentration at the harbour, and tables for alerting and advising ship personnel on the likelihood of such an event based on offshore winds, surface ocean currents, and ice conditions. These events are primarily controlled by the strength and character of an ocean current gyre and the ice conditions over a large area offshore St. John’s Harbour.

Lifeboats are a ubiquitous means of evacuation fitted to offshore petroleum installations and marine vessels. For lifeboats operating in ice environments, the magnitude of local ice loads and the structural integrity of these crafts under ice loading are not well understood. To address these gaps, full-scale measurements relating to lifeboat-ice interactions were collected during a field campaign carried out in 2013. During this trial, the local ice loads on the hull of a Totally Enclosed Motor Propelled Survival Craft (TEMPSC) operating in pack ice conditions were measured using instrumented load panels. This full-scale field data provides the foundation for risk-based design load estimation and has been analyzed using the event-maximum method of local ice pressure analysis. This approach is based on probabilistic methods developed for the analysis of ice loads measured on icebreakers, which have been adapted for ice interaction scenarios involving small vessels. Results from this work provide improved insight into the nature of loads on lifeboats operating in ice-covered waters and help to inform design methodology for these vessels.

For temperate ice regions, the guidance provided by current design codes regarding ice load estimation for thin ice is unclear, particularly for local pressure estimation. During the non-simultaneous failure of ice under compression, spalling fracture localizes contact into high pressure zones (hpzs), through which the majority of loads are transmitted. Much of our present understanding of hpzs comes from inferences made from the analysis of pressure panel data collected during medium-scale field tests or full-scale measurements on ships or structures. During medium-scale field indentation tests conducted by the Japan Ocean Industries Association (JOIA) from 1996-2000, tactile pressure sensors were also deployed. The JOIA dataset provide detailed information about pressure distributions at a sufficiently high resolution so as to allow for the identification and tracking of individual hpzs throughout an interaction. Given their importance in the transmission of loads during an ice-structure interaction, understanding the birth, evolution and death of individual hpzs is seen as being an important direction both for guiding fundamental studies of ice mechanics and also for guiding the development of new ice load models. Recent analysis of these tactile sensor data has led to the development of an empirical hpz-based model which can be applied to model local and global pressures for thin ice conditions (Taylor and Richard, 2014). From this analysis, new insights into the nature of hpzs for thin first year sea ice during non-simultaneous failure have resulted. In the present paper, an overview is provided of analysis techniques used to extract information about individual hpzs from the tactile sensor dataset, as well as the characteristics of these hpzs. Aspects discussed include spatial and temporal characteristics of high pressure zones, as well as pressure and geometric attributes. While observations of the shape of spatial distributions and total contact area covered by hpzs are consistent with previous observations (line-type distributions with total contact area on the order of 10% of the nominal interaction area), these results indicate that individual hpzs are smaller and more densely distributed than indicated by previous analyses based solely on pressure panel data. The implications of this finding in terms of scale effects and ice load modeling are discussed.