Performance of steel moment-resisting frames in post-earthquake horizontally traveling fire
Bibliographic record
Abstract
Purpose The study investigates the performance of a three-story unprotected steel moment-resisting frame (SMRF) designed for high seismic demand in the fire-only (FO) and post-earthquake uniform and traveling fires (PEF). The primary objective is to investigate the effects of seismic residual deformation on the structure's performance in horizontally traveling fires. The traveling fire methodology, unlike conventional fire models, considers a spatially varying temperature environment. Design/methodology/approach Multi-step finite element simulations were carried out on undamaged and damaged frames to provide insight into the effects of the earthquake-initiated fires on the local and global behavior of SMRF. The earthquake simulations were conducted using nonlinear time history analysis, whereas the structure in the fire was investigated by sequential thermal-structural analysis procedure in ABAQUS. The frame was subjected to a suite of seven ground motions. In total, four horizontal traveling fire sizes were considered along with the Eurocode (EC) parametric fire for a comparison. The deformation history, axial force and moment variation in the critical beams and columns of affected compartments in the fire heating and cooling regimes were examined. The global structural performance in terms of inter-story drifts in FO and PEF scenarios was investigated. Findings It was observed that the larger traveling fires (25 and 48%) are more detrimental to the case study frame than the uniform EC parametric fire. Besides, no appreciable difference was observed in time and modes of failure of the structure in FO and PEF scenarios within the study's parameters. Originality/value The present study considers improved traveling fire methodology as an alternate design fire for the first time for the PEF performance of SMRF. The analysis results add to the much needed database on structures' performance in a wide range of fire scenarios.
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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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".