Overwintering of barges in the Beaufort - assessing ice issues and damage potential
Bibliographic record
Abstract
Overwintering of vessels and barges has been carried out in the Arctic for many years, in the Beaufort as well as in other regions of the Arctic and southern Canada. Draft guidelines from Transport Canada exist for this practice. However, there is uncertainty concerning the damage potential for structures that may be left to freeze-in within the landfast ice region of the Beaufort Sea, particularly those that contain petroleum products. This is a great concern for the Inuvialuit, among others. There is evidence that this freeze-in could be (and has been) done safely but it is not clear how often this has been done or the conditions required to ensure safe overwintering of vessels in the Beaufort Sea. No information exists on the likelihood of damage due to ice or its possible effects. A detailed study focused on the conditions of the Beaufort Sea would greatly aid many stakeholders on the magnitude of this problem and its possible impact. This study brought together different types of relevant data and information to resolve this important issue, with a focus on the ice loading considerations. As such, the objective of this project was to assess the damage potential for vessels or barges overwintering in land-fast ice. The project will inform the Inuvialuit and Regulators on the likelihood of damage and provide information on the best-available means of reducing the likelihood of damage to vessels overwintering in ice in the nearshore region of the Beaufort Sea. The report steps through illustrative scenarios, in order to provide examples of the types of ice loads that could occur in representative overwintering locations. These scenarios lead to the provision of a framework of methods used to evaluate ice loads on vessels. This framework can be applied to assess ice loads on a specific vessel with known structural integrity at a specific location, by a team of qualified operational, ice mechanic and naval architect experts. No design considerations are provided, as that assessment would be too case specific to be of use in an overview of this subject area. The authors conclude that a sheltered spot, with a limited fetch area, to limit pack ice driving forces is a key factor to minimizing the likelihood of damage due to ice. It is not sufficient to say that a vessel will be in landfast ice conditions throughout the winter. There are many locations where a vessel may be in landfast ice conditions for most of the winter, but the vessel may be in dynamic conditions come the spring break-up period. During this period, depending upon the location, ice crushing forces on a vessel and/or ice loads can be sufficient to break mooring lines and potentially damage a vessel. Thus, the overwintering location should have minimal dynamic ice movement in the spring, to avoid this scenario. Finally, in order to partially alleviate concerns about the practice of overwintering, and more specifically, overwintering of fuel barges, the authors recommend that the Inuvialuit Settlement Region implement their own record-keeping of fuel barges that are overwintering. This would take the form of a simple record of location, vessel and contact information. Having a record of overwintering, and a method of tracking it, may help to provide more data on the practice, guidance on best practices related to overwintering (such as notification for affected communities and those travelling in the vicinity of the vessel), and peace of mind in terms of sound site selection practices and monitoring.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".