Effect of Preliminary Selection of RC Shear Walls' Ductility Level on Material Quantities
Bibliographic record
Abstract
According to the National Building Code of Canada, the seismic force resisting systems (SFRS) of reinforced concrete (RC) buildings are classified based on their ductility level as being ductile, moderately ductile and conventional construction systems. The selection of the ductility level of an SFRS at the conceptual design phase is primarily governed by the seismicity at the building location, the building dynamic characteristics, and the height limitations specified by the design code. The selected ductility level affects the design loads, the cross-sections and reinforcement of the SFRS components, and hence the overall construction cost. This paper aims to evaluate the effect of the wall's selected ductility level on the quantities of its constituent materials as well as the rebar detailing. Four multi-storey RC shear wall buildings with different heights located in three different cities in Canada; Toronto, Montreal, and Vancouver, were selected to represent three different seismic hazard zones (low, medium, and high). For each building height and location, the walls were designed using the dynamic analysis procedure of the National Building Code of Canada to reach different ductility levels. The construction material quantity estimates were evaluated and compared to a reference case for each building height, seismic hazard and ductility level. The effect of ductility level on the bars detailing is also investigated. This paper helps the structural engineers to select the cost-effective and constructible RC shear wall system at the conceptual design phase before reaching the detailed design phase.
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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 | 0.005 |
| 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 | 0.001 | 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".