Near‐fault acceleration pulses and non‐acceleration pulses: Effects on the inelastic displacement ratio
Bibliographic record
Abstract
Summary Near‐fault ground motions can impose particularly high seismic demands on the structures due to the pulses that are typically observed in the velocity time‐histories. The velocity pulses can be further categorized into either a distinct acceleration pulse ( acc‐pulse ) or a succession of high‐frequency, one‐sided acceleration spikes ( non‐acc‐pulse ). The different characteristics of velocity pulses imply different frequency content of the ground motions, potentially causing different seismic effects on the structures. This study aims to investigate the characteristics of the two types of velocity pulses and their impacts on the inelastic displacement ratio ( C R ) of single‐degree‐of‐freedom systems. First, a new method that enables an automated classification of velocity pulses is used to compile a ground motion dataset which consists of 74 acc‐pulses and 45 non‐acc‐pulses . Several intensity measures characterizing different seismological features are then compared using the two groups of records. Finally, the influences of acc‐pulses and non‐acc‐pulses on the C R spectra are studied; the effects of pulse period and hysteretic behavior are also considered. Results indicate that the characteristics of the two types of velocity pulses differ significantly, resulting in clearly distinct C R spectral properties between acc‐pulses and non‐acc‐pulses . Interestingly, mixing acc‐pulses and non‐acc‐pulses can lead to local “bumps” that were found in the C R spectral shape by previous studies. The findings of this study highlight the importance of distinguishing velocity pulses of different types when selecting near‐fault ground motions for assessing the nonlinear dynamic response of structures.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 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".