Effect of Axial Compression on Flexural Strength of Freshwater Ice
Bibliographic record
Abstract
Abstract In the design of bridges, wind turbine towers, offshore structures and ice-class ships for operations in ice-prone regions, sloped structures may be employed to promote flexural failure of level ice to reduce loads on the structure. During such interactions, the ice sheet does not fail in pure bending since a component of the applied force at the sloped interface results in an axial load that induces a compressive stress in the ice. The net effect of this axial component is that the corresponding compressive stresses balance with flexure-induced tensile stresses in the outmost fibres of the ice. As a result, the apparent flexural strength of the ice is expected to increase with increasing axial compression, since larger bending forces would be required to generate sufficient tension to trigger fracture. In ice load prediction models for sloped structures, an in-plane compression (IPC) factor is applied to calculated loads to account for increased flexural strength which is empirically determined to be 1.5. While the method of superposition may be used to assess combined loading effects for elastic structures, assessing such effects in ice is more complex since the behaviour of ice is not purely elastic. In this paper, the relationship between axial compression and the flexural strength of freshwater ice is studied experimentally to assess how the flexural failure behaviour of the ice changes for different levels of in-plane compression factor. A series of experiments on freshwater ice have been conducted for compression levels at 75%, 135% and 185% of unconfined flexural strength for ram speeds of 0.1 mm/s, 1.0 mm/s and 10.0 mm/s. These results indicate that in-plane compression significantly increases the apparent flexural strength of the ice, highlighting the need for further work in this area to better understand this phenomenon and assess implications for design. This new testing approach provides a promising direction for further examination of these important effects, including extending this work to the analysis to sea ice and to consider lower IPC values.
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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 | 0.001 |
| 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) | 0.003 | 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 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".