Structural irregularity: The analysis of two reinforced concrete (r.c.) buildings
Bibliographic record
Abstract
Structural irregularity is a crucial issue in assessing seismic vulnerability of both new and existing buildings. European technical codes provide simple criteria to define irregularities in plan and in elevation, amplifying the seismic actions and/or introducing torsional effects. Nevertheless, this approach only considers geometrical irregularity. For existing buildings, another source of irregularity comes from the non-uniform distribution of the material strength. In particular, for existing reinforced concrete (r.c.) structures, it is possible to detect significant spread of the concrete compressive strength not only from different structural elements but also from different parts of the same member. In this work, non-linear static analysis is performed on two case-studies of r.c. buildings characterized by geometrical and mechanical irregularity. The resistance of each column is determined with an extensive experimental campaign with in situ and laboratory test (about 600 in situ tests). The results are analyzed considering both local and global effects in terms of resistance of the single elements and of the entire buildings. In this sense, shear and bending failure mechanism are taken into account. The effect of storey flexibility is also considered in the models. Fragility curves are calculated for the buildings with random distribution of the compressive strength of the columns. The results are then compared with the approaches proposed by the Eurocodes evaluating in the standard approach proposed by technical codes is conservative or not.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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".