O.I.C.-based design of steel rectangular hollow sections at high temperatures
Bibliographic record
Abstract
This paper investigates the fire resistance of hot-rolled rectangular and square hollow sections at the cross-sectional level. Advanced non-linear Finite Element models are developed and validated against 17 well-documented tests, covering Class 2 (plastic) and Class 4 (slender) tube sections under combined compression and bending from 20°C to 700°C. The strong correlation between numerical and experimental results confirms the accuracy of these models, which are then used to analyze cross-sectional fire behavior and resistance. Over 1 400 non-linear simulations assess the influence of cross-sectional geometry, temperature, and loading conditions. A novel design approach based on the Overall Interaction Concept (O.I.C.) is introduced, offering a simplified yet highly accurate method for design verification. Compared to Eurocode 3, A.I.S.C., and C.S.A.-S16 standards, which tend to be either overly conservative or unsafe, the O.I.C. method provides superior precision and reliability. Reliability analyses further demonstrate that the O.I.C. approach meets and exceeds the required safety levels, making it a more effective alternative for fire-resistant structural design.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".