Water/ice loads and scour at Canadian bridges in a changing climate: state of practice review
Bibliographic record
Abstract
The federal government, through Infrastructure Canada (INFC), has established the Climate Resilient Buildings and Core Public Infrastructure (CR-B&CPI) Project led by the National Research Council (NRC). A key project objective is to develop new and updated codes, guides and standards to support the design and rehabilitation of buildings and infrastructure to achieve improved climate resilience. To support meeting this objective, NRC’s Ocean, Coastal and River Engineering (OCRE) Research Center reviewed the current state of practice in Canada and internationally for evaluating water loads, scour and ice action, and related climate change impacts, on bridges and overpasses. The objectives of the initial literature review were to: -Identify and review recent cases of bridge damage/failure due to water loads, scour or ice loads in Canada and internationally; -Review the evolution, and current status, of methods and approaches to evaluating water loads, scour and ice action for new bridges presented in recent research publications, codes and standards; -Review recent research on approaches to incorporating climate change impacts (and associated changes in the frequency and intensity of extreme weather events) in methods of evaluating water loads, scour and ice action for new bridges; -Identify and summarize possible adaptation strategies and design approaches or practices currently in use to mitigate ice loads, water loads and scour at bridges in Canada and internationally. Historical failures in Canada and elsewhere highlight the risks posed by water loads, scour and ice effects to bridges, with more than half of bridge failures in North America attributed to floods and hydraulic factors; particularly scour. River ice is a particularly relevant hazard for Canadian bridges and associated structural components, with most rivers having seasonal ice cover. Estimates of annual average damages in Canada due to ice jams exceed $100 million. High-profile bridge collapses and damaging events have motivated much of the research forming the current basis for assessing water loads, scour and ice action on bridges. The risks associated with climate change, in terms of the increasing exposure and vulnerability of bridges and overpasses to water and ice hazards, represent growing concerns for Canadian infrastructure owners. A review of provisions in the Canadian Highway Bridge Design Code (CHBDC) for assessing water loads, scour, and ice action – and comparisons to various other standards, codes and guidelines in use in Canada and internationally – identified potential opportunities for improvements in future design guidance. These include opportunities to re-evaluate or re-consider some design aspects and approaches to load assessment for bridges as described below:
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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 | 0.012 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.010 |
| Open science | 0.002 | 0.003 |
| 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".