Horizontal and Vertical Seismic Acceleration Demands in Multi-Storey Buildings
Bibliographic record
Abstract
Accurate prediction of peak floor accelerations is a crucial step in developing simplified methods for the seismic analysis and vulnerability estimation of acceleration-sensitive non-structural components (NSCs) attached to buildings subjected to earthquakes. A particular characteristic of seismic floor accelerations is that they increase along the building height, with a maximum amplification at the rooftop level. While the amount of horizontal acceleration amplification currently suggested in most modern building codes is empirical, the amount of vertical acceleration amplification is not fully addressed yet in most building codes. This paper discusses the amplification of horizontal and vertical rooftop accelerations based on the analysis of recorded accelerations in 7 buildings during the 1999 Chi Chi earthquake in Taiwan. The ratio between vertical and horizontal rooftop accelerations and spectra is also discussed. Evaluated parameters affecting the amplification of vertical accelerations include: the building vertical period of vibration, the number of stories, and the location of the building relative to the fault. Findings are discussed and compared to provisions currently proposed in the ASCE 7, the NBCC 2015, the CSA S832 and the Eurocode 8. The most significant trends are highlighted.
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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 | 0.001 |
| 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".