Performance of reinforced concrete columns in fire and under extreme forces
Bibliographic record
Abstract
This presentation provides information on the ongoing studies on performance evaluation of reinforced concrete columns in fire and extreme forces. NRC-IRC has been investigating a new fire resistance testing approach that will consider the effects on a whole building, rather than just individual elements, by using analytical and computer simulations. This new approach is being developed for use in estimating the fire-resistance of reinforced concrete columns, within a building frame, taking into consideration the effect of the structural system, thermal expansion and lateral loads. A brief introduction of this new testing method will be provided. Furthermore, studies have been explored on performance assessment of columns in fire and under extreme forces such as an earthquake. This includes post-earthquake fire performance evaluation of reinforced concrete columns and post-fire seismic resistance of reinforced concrete columns. Investigation on the first subject is being carried out. A study on the second subject has been completed on assessment of the residual strength and lateral/seismic load capacity of reinforced concrete columns after fire exposure. The results will be presented in brief along with a future research on blast and fire.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".