Performance based seismic assessment of bridges designed according to Canadian Highway Bridge Design Code
Bibliographic record
Abstract
Recent research efforts have focused on the development of performance based seismic design methodologies for structures. However, the seismic design rules prescribed in the current Canadian Highway Bridge Design Code (CHBDC) is based largely on force based design principles. Although a set of performance requirements (performance objectives) for different return period earthquake events have been specified, there is no explicit requirement in the CHBDC to check the attainment of such performance objectives for the designed bridges. Also, no engineering parameters have been assigned to the specified performance objectives. This paper correlates seismic performance objectives (both qualitative and quantitative) with engineering parameters, based on the data collected from published experimental investigations and field investigation reports of recent earthquakes. A simple method has been developed and validated with experimental results for assessing the performance of bridges designed according to CHBDC. It has been found that the design rules prescribed in CHBDC do not guarantee that specified multiple seismic performance objectives can be achieved. An implicit seismic design rule in the form of performance response modification factor has been outlined for the performance based seismic design of bridges.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".