10.22: Comparing the fire behaviour of composite columns made with concrete filled double‐skin and double‐tube steel sections
Bibliographic record
Abstract
ABSTRACT The use of composite concrete filled hollow columns has increased in the last decades. This type of column has several advantages, such as the exemption of using formworks, a higher load bearing capacity and the prospect use of smaller cross sections. Although it has a good behaviour in fire situation, the use of slender columns, mainly in tall buildings, makes necessary to find solutions for increasing the fire resistance. In this sense, this paper presents a comparative experimental study on the fire resistance of composite columns made with concrete filled double‐skin and double‐tube steel sections and with restrained thermal elongation. A set of fire resistance tests, on a special set‐up, were carried out. The double‐tube columns had two steel tubes, one external and one internal, with approximately half the diameter of the outer tube, both tubes were concrete filled. The double‐skin columns had also two steel tubes, but the inner tube was void. Several parameters were investigated, such as the load level, stiffness of the surrounding structure and type of concrete infill. The paper presents results for fire resistance, restraining forces, axial deformation and deformed shapes of the tested columns.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
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".