Conical Structures in Ice: Relevant Relationships for ISO 19906
Bibliographic record
Abstract
Conical shapes are often chosen for structures that are exposed to floating ice, such as offshore drilling platforms, bridge piers and offshore wind turbine foundations. The flexural ice failure promoted by the shape of a cone can lead to lower forces on the structure than compressive failure, which would take place if ice is to encounter a vertical surface. In spite of the wide use of conical structures, many aspects of their performance in ice covered waters remain poorly understood. For example, the ISO 19906 Arctic Offshore Structures standard does not provide guidance with respect to ridge keel loading on cones, or the height to which ice could ride up on a conical structure. With the planned revision of that document presently beginning, it is important to address the guidance gaps in order to include new insights in the revised standard. Previous work by the authors employed a numerical model of ice dynamics in order to predict ice failure patterns and forces on various conical structures. The present work extends those studies and predicts the extent of ice ride-up on the structures; the roles of the waterline width of the structure and ice thickness are discussed. The resulting ice force estimates are comparable to those predicted by an approach recommended in ISO 19906. Both the plastic and elastic beam-bending methods recommended by ISO 19906 for determining ice actions on conical structures require an initial assumption of the maximum height of accumulated rubble. Little guidance is given in ISO 19906, except to note that this height depends on the structure geometry and ice regime. For the present calculations, the chosen rubble height for each ice load calculation is based on the results of the corresponding numerical model run. Previous numerical studies by the authors have also been reviewed and the estimates of ice ride-up heights summarized. Numerical simulations could be expanded to produce a comprehensive range of ride-up values to support users of ISO 19906.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".