Ice wear and abrasion of marine concrete: design of experimental apparatus and procedures
Bibliographic record
Abstract
Abrasion of marine concrete structures from passing ice is an ongoing problem that leads to loss of structural integrity over time. The purpose of this study is to develop new experimental approaches and apparatus that would allow long term testing of ice wear on concrete samples as a prelude to a larger study that will investigate the wear of concrete by ice. This thesis has drawn on the experiences of previous work to identify the important issues, including those areas where different approaches may be beneficial. A review has been completed of previously used tests setups, contributing factors and areas of uncertainty. This has resulted in two conceptual designs that approach the problem from slightly different angles. The first is a lab scale apparatus that aims to standardize the testing methods for concrete wear due to ice. The conceptual design of a new apparatus will allow wide ranging load applications, long test durations and the inclusion of surrounding water. The second is an in-situ apparatus that has been developed to allow direct comparison between concrete mixtures in terms of wear resistance under realistic but uncontrolled ice conditions. Pilot experiments have been completed and reviewed to refine the initial concept and to determine effective means of abrasion measurement. These experiments provided insight into important features of the designed apparatus, trial results from measurements of iceinduced wear on concrete and useful information on concrete wear experiments in general.
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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 | 0.006 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".