Fire Performance of FRCM-Confined RC Columns: Experimental Investigation and Parametric Analysis
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Bibliographic record
Abstract
This study presents an experimental investigation of the fire response of six columns strengthened with polyparaphenylene benzobisoxazole (PBO) FRCM system, and tested in a large-scale furnace following ASTM E119 standards. The parameters investigated included the number of PBO-FRCM layers and the presence of a fireproofing insulation layer. Test results highlighted the effectiveness of PBO-FRCM in insulating the column, with the strengthened column showing a substantial 31.9% reduction in temperature readings at the concrete surface compared to its unstrengthened counterpart. Furthermore, the presence of Sikacrete 213F fireproofing system reduced temperature readings within the column's section by an average of 65%. Based on the experimental results, a parametric numerical study were developed and verified using ABAQUS software. The parameters studied included the number of PBO-FRCM layers (0, 1, and 2 layers), the presence of a 30 mm thick insulation layer, and the axial preloading taken as 40, 60, and 75% of the ultimate column's capacity. The model accurately predicted the temperature readings across the columns. Strengthening the columns with PBO-FRCM significantly increased their resistance during fire, doubling fire-resistance duration with one layer. Adding fireproof insulation led to significant increase in load resistance duration. The percentage drop in temperature after 1 hour of fire exposure was around 70% at the FRCM surface for the insulated column strengthened with one layer of FRCM. Higher preload percentages reduced both the fire-resistance duration and ductility of the columns. For the group of columns strengthened with one layer, increasing the preloading percentage to 60% and 75% resulted in decreases in the fire-resistance duration of 35% and 73%, respectively.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it