Application of the POLARIS methodology to historic ice-class ship operations in freshwater lake ice
Notice bibliographique
Résumé
The primary objective of this work is to examine ship operations in freshwater versus sea ice in the context of evaluating appropriate regulatory guidelines, through analysis of historic data for the North American (Laurentian) Great Lakes region, a heavily trafficked freshwater waterway that is crucial for the functioning of Canada’s industrial heartland. The first goal of this analysis was to characterize expected ice conditions that could be found within the region through aggregating and sampling data from Canadian Ice Service ice charts over the 10-year study period, which includes the ice seasons from 2010 to 2019. This was followed by an analysis of ship traffic in the region during the same period through the use of historical archived AIS data. Lastly, the POLARIS methodology, an internationally accepted means of guiding ship operators in specific sea ice conditions, was applied to the historic ship operations described by the available AIS data to provide a comparison of historic operator decisions in lake ice to existing guidelines for operations in sea ice of similar thickness and concentration. The characterization of the regional ice conditions during the studied period was intended to provide additional context for the ship traffic analysis for comparison against typical local ice conditions along shipping routes. As existing reviewed literature previously indicated, this analysis clearly affirmed that there is significant year-to-year variability in the potential severity and duration of a given ice season in the Great Lakes. Results obtained from the analysis of historic ship traffic in the region and the application of the POLARIS methodology to this data provided valuable insights into the nature of current ship operations in ice in the Great Lakes. Overall, the trends observed suggest that current practices are well aligned with POLARIS guidelines for sea ice (89% of ice operations are in positive RIO values) and that risk mitigating measures currently used in the Great Lakes (such as icebreaker support and speed reductions when transiting through ice) are compatible with the approaches recommended in POLARIS. However, it is recommended that a more detailed analysis of the correlation between historical ship operations and icebreaking activity in specific regions be conducted to provide a better understanding of the degree to which ships operate in managed ice conditions. Further exploration of the POLARIS guidelines in the context of adapting mitigating measures into operational guidance for freshwater ice is also recommended, given the known differences in material properties of sea ice versus freshwater ice. Since it is not evident how such differences in ice types would translate into differences between the current POLARIS method and a modified “Freshwater POLARIS”, additional research is needed to assess the impact of differences in ice properties in terms of potential for ship damage and appropriate speed limits, as well as assessing the need for possible modification of Risk Index Values for lake ice types. In summary, the results of this work do suggest that the development of specifically tailored POLARIS-like guidelines presents a promising approach to aid ship operations in lake ice conditions similar to that found within the Laurentian Great Lakes during the studied 10-year period. The potential to codify current best-practices for shipping operations in the Great Lakes into such a modified method would help ensure consistency in the assessment of operational capabilities and limitations for different classes of vessels operating in lake ice. This in turn would provide greater clarity regarding expected mitigating measures and would help support effective decision-making relating to ship operations in ice.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,005 | 0,005 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».