Performance of a six-story reinforced concrete structure in post-earthquake fire
Bibliographic record
Abstract
This paper presents results of a 3D performance simulation of a six-story reinforced concrete structure exposed to a fire after the shaking table test for the Kobe Earthquake 1995. The structural analysis software, SAFIR, capable of 3D simulation of building structures in fire, was employed to evaluate performance of the building under fire. The ASTM E119 standard fire was selected as the fire load for this study. In order to consider the effects of damages to the structural elements during the earthquake, degradation of material mechanical properties and heat penetration, due to cracks, were considered for the post-earthquake fire analysis. The fire was assumed to have occurred on the ground floor next to the short columns that experienced considerable damage during the earthquake. A comparison study was implemented to investigate effects of material degradation and heat penetration on the fire resistance of the building after the earthquake.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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) | 0.011 | 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; both teacher heads agree on what is shown here.
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".