Generating Spectrum‐Compatible Time Histories Using Eigenfunctions
Why this work is in the frame
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Bibliographic record
Abstract
In this article, the causes of drift in the velocity and the displacement time history are investigated. It is found that, in addition to numerical error, drift is caused by overdeterminacy in the constants of integration. Because there are six independent prescribed at‐rest conditions (three initial and three terminal), the eigenfunctions from an eigenvalue problem, which is described by a sixth‐order ordinary differential equation satisfying the six initial and terminal at‐rest conditions, are chosen as a basis of expansion. The eigenfunctions form a dense and complete set and span a vector space. The eigenfunctions are used to expand an accelerogram. Drift‐free consistent velocity and displacement time histories are then obtained, also in terms of the eigenfunctions, without direct integration and baseline correction. A method is also proposed to modify a real recorded accelerogram using the eigenfunctions to generate time histories compatible with the target response spectra without drift.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it