A Novel Approach to the Integration for Generating Consistent Ground Acceleration, Velocity and Displacement Time Histories
Bibliographic record
Abstract
The velocity and the displacement time history obtained by directly integrating the acceleration time history will drift unrealistically because of the over-determinacy of the integration constants. Applying baseline corrections to resolve drift disturbs the frequency content and renders the corrected processes mutually inconsistent. In this study, eigenfunctions of sixth-order eigenvalue problem are introduced as basis functions for decomposing recorded ground motion time history. Taking advantage of the eigenfunctions and their first two order of differentiations are drift-free and consistent, the decomposed and reconstructed acceleration, velocity, and displacement time histories can be drift-free and mutually consistent without direct integration and baseline correction. Two earthquake ground motions are presented as examples, which show that the decomposed acceleration, velocity, and displacement time histories are drift-free, mutually consistent, and almost the same as the seed motion. The new approach can replace integral in the generation of velocity and displacement time histories.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".