ASSESSMENT OF COLLAPSE SAFETY OF TORSIONAL SENSITIVE STEEL BUILDINGS UNDER BIDIRECTIONAL EXCITATIONS
Bibliographic record
Abstract
Post-earthquake investigations showed that torsion-induced damage was among the causes of buildings collapse. In previous studies, researchers observed that accidental torsion could cause yielding of one braced frame, which, in turn, changes the center of rigidity toward the undamaged frame by increasing the inherent eccentricity with respect to the center of mass, CM. To account on these effects and those induced by bidirectional excitation and other sources, accidental torsion caused by accidental eccentricity (ea) was introduced in building codes to increase member sections resisting storey shear. The current Canadian National Building Code (NBC) considers accidental torsion caused by ea = ±10%Dnx, where Dnx is the plan dimension of the building at level x perpendicular to the direction of seismic loading. According with NBC provisions, a building is classified as torsionally sensitive, if the ratio Bx is greater than 1.7. Nonetheless, for regular buildings, the code allows considering ea = ±5%Dnx if dynamic analysis is employed. According to ASCE/SEI 7-16 standard, the torsional moments are computed for ea = ±5%Dnx, but for torsionally sensitive buildings, these are multiplied by a torsional amplification factor Ax. It is worth mentioning that a symmetric building that has relatively low torsional stiffness could be torsionally sensitive. To emphasize on the correlation between the predicted displacements caused by torsional moments induced by ea and those resulted from nonlinear response history analysis, the need for a detailed 3D building model emerged. The objectives of this paper are: i) to quantify the effect of accidental torsion considered in seismic design, by assessing the collapse safety of steel braced frame buildings, using detailed 3D building models, ii) to assess the effect of bidirectional excitation on the nonlinear seismic response of regular and torsionally sensitive buildings, and iii) to evaluate the strength and deflection criteria of torsionally sensitive steel buildings. The case study is a 4-storey concentrically braced frame (CBF) office building with a square floor plan and various CBFs locations leading to various Bx ratios. The distribution of inelastic demand is analysed in terms of interstorey drift, residual drift and floor acceleration, measured at the extreme points of building floor and CM. Considering incremental dynamic analysis, the collapse safety criterion is verified and discussed.
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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 | 0.001 | 0.001 |
| 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 | 0.001 |
| 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".