Seismic performance of a full-scale, reinforced high-performance concrete building. Part I: Experimental study
Bibliographic record
Abstract
Full-scale tests provide valuable information on the characteristics of building structures that can be used to evaluate design methods, to calibrate modelling techniques, and to determine damage corresponding to loading levels. These tests are scarce due to the enormous requirements in testing space and specialized testing equipment. The seismic behaviour of a full-scale, two-storey, reinforced high-performance concrete building designed with moderate ductility detailing is evaluated by pseudo-dynamic testing, during which increasing seismic loads are applied, resulting in increasing levels of permanent damage to the structure. To monitor the level of damage, a series of successive forced-vibration tests are also carried out at each step of the process and are used to track changes in the key dynamic properties of the building. The paper presents the design of the test structure according to the new edition of the CSA A23.3-04 Design of concrete structures standard, the series of pseudo-dynamic tests simulating different levels of earthquake excitation consistent with the 2005 edition of the National building code of Canada, and the evaluation of the performance of the building. It is shown that the detailing requirements of CSA A23.3-04 are more than adequate to provide the ductility and overstrength expected.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".