Seismic microzonation and vulnerability of highway bridges in Montreal
Bibliographic record
Abstract
Ground Ambient Noise (GAN) readings were recorded across the island of Montreal and the recordings were processed using the horizontal-to-vertical spectral ratio technique. One-dimensional non-linear soil dynamic analyses were performed over a large database of boreholes in Montreal using the computer program SHAKE. The resulting predominant frequencies of vibration were used as the main parameter to define the seismic microzonation of the island of Montreal. The frequencies are mapped and used to identify twelve zones with potential seismic amplification problems. The largest ratio was obtained in the zone located at the eastern tip of the island of Montreal where long-period motions are predominant in the deep clay deposits. The Incremental Dynamic Analysis (IDA) technique was used to study the seismic vulnerability of two typical lifeline highway overpass bridges in Montreal. The moment resisting frame components of the two bridges were studied and evaluated for different cases reflecting the condition of the concrete columns and their reinforcement, in accordance with the Canadian Highway Bridge Design Code (CHBDC). The frames were subjected to a wide range of earthquakes as part of the IDA study. The insufficient shear reinforcement of some frame elements of both bridges predicted a premature shear failure, which controlled the seismic behaviour of the frames. The predicted failures occurred at a lower spectral acceleration level than the acceleration specified by the CHBDC for both lifeline bridges. A minimum-intervention retrofitting approach was devised for each one of the overpass bridges. In both cases, provisions were made to ensure that flexural yielding would occur before shear failures of the critical elements. The retrofitted frames are predicted to sustain higher levels of spectral acceleration in excess of 0.8 g.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".