A Three-Dimensional Model for Ice Rubble Pile-Ice Sheet-Conical Structure Interaction at the Piers of Confederation Bridge, Canada
Bibliographic record
Abstract
Offshore structures constructed in waters where ice cover is prevalent for several months a year are subjected to ice loading. Some of these structures are conical or sloped-faced in shape, where flexural failure becomes the dominant mode of failure for the ice sheet. The flexural failure mode reduces the magnitude of ice-structure interaction loads in comparison to other modes of failure. Various researchers have devised flexural failure models for ice-conical structure interactions. Each model shares the same principle of the ice sheet being modeled as a beam on an elastic foundation, but each model has different limitations in precisely simulating the interaction. Some models do not incorporate the ice rubble pile, while other models make oversimplified assumptions for three-dimensional behavior. The proposed three-dimensional (3D) model aims to reduce some of these limitations with the following features: (1) modeling the geometry of the ice rubble pile around the conical pier using the results of small-scale tests, (2) modeling the loads exerted by the ice rubble pile on the conical structure and ice sheet with a rigorous method of slices, (3) adding driving forces in keeping the rubble pile intact and in upward motion during the interaction, (4) accounting for eccentric offsetting moments at the ice-structure contacts, and (5) modeling the flexural behavior of the ice sheet subject to ice rubble loads using finite element method. The proposed model is used to analyze the interaction events recorded at the conical piers of the Confederation Bridge over a period of 11 years.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".