TOWARDS SEISMIC RESILIENCE OF PRECAST COLUMN-TO-PILE SHAFT ASSEMBLIES AMID CLIMATE CHANGE
Bibliographic record
Abstract
The burgeoning maintenance backlogs in Canadian bridge infrastructure underscores the need to adopt Prefabricated Bridge Elements and Systems (PBES) as a means of relieving this burden. PBES can offer substantial time and cost savings for repairs and replacements. Among the key contributors to a bridge's seismic behaviour is the substructure PBES, with a particular focus in this paper on the precast column-to-pile shaft assembly as a substructure PBES type. Climate change-induced structural deterioration is accelerating, introducing significant uncertainties into the seismic performance of aging bridge substructures. The combined impacts of climate change, deterioration, and seismic activity on the precast column-to-pile shaft assembly have thus far received limited investigation. The objective of this current paper is to assess the impact of corrosion on the seismic performance of precast column-to-pile shaft assemblies, taking into account the influence of climate change. To achieve this, key design parameters were initially determined to assure the formation of a plastic hinge at the column's base during seismic events, while maintaining the elasticity of the pile shaft. The effectiveness of the seismic design was verified through moment-curvature analyses and finite element simulations. The effects of climate change on corrosion, including early initiation and accelerated material degradation, were incorporated into the corrosion model, considering environmental factors like temperature and relative humidity. The degradation mechanisms in both columns and pile shafts, such as loss of reinforcement section and material property degradation were modelled. Finally, the analysis findings were synthesized to inform the climate change impacts on the time-dependent seismic resistance, including variations in moment strengths and failure modes.
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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 | 0.001 |
| 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".