Automated parameterization of velocity pulses in near‐fault ground motions
Bibliographic record
Abstract
Abstract Proper parameterization of near‐fault ground motions is of critical importance in earthquake engineering, and this process is traditionally performed by directly fitting an analytical pulse model to the original motion. Yet such a process is usually limited by the trial‐and‐error procedure, which is strongly dependent on the initial guesses and may converge to local rather than global minimums. In this study, we propose a progressive (step‐by‐step) iterative approach that can achieve a fully automated parameterization of the velocity pulse contained in near‐fault motions. Assuming that a velocity pulse can be characterized by a pulse model with four key parameters, the approach is conducted by iteratively matching the pulse model to the smoothed ground motion, and the parameterized pulse is analytically derived by best fitting to the smoothed motion not only in the time domain but also in the spectral domain. Specifically, the velocity time history of interest is initially smoothed by a moving average filter so that the low‐frequency content can be filtered out of the original motion, from which the pulse amplitude as well as its epoch is accordingly determined. The coherent velocity pulse is then progressively extracted by performing the nonlinear least‐square‐fitting of the pulse model to the filtered low‐frequency content, during which the remaining parameters, that is, the pulse period, the number of cycles and the phase of the pulse, are estimated successively. Finally, the above procedure is applied repeatedly to the original ground motion by changing an empirical factor controlling the extent of smoothing of the motion so that convergence to local minimums that frequently occurs in the trial‐and‐error procedure could be largely avoided, and best match of the spectrum of the extracted pulse to that of the original motion can be acquired. Fitting quality of the velocity pulses is examined by comparing with existing methods. Prospective applications of the proposed procedure include the stochastic simulations of near‐fault ground motions and parametric investigations of the influence of velocity pulses on various engineered 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 | 0.002 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".