On the “elastic stiffness” in a high-cycle accumulation model — continued investigations
Bibliographic record
Abstract
The high-cycle accumulation (HCA) model proposed by the authors can be used to predict permanent deformations or stress relaxation due to a large number (e.g., several millions) of load cycles with relative small strain amplitudes (<10−3). The predicted stress relaxation depends on the isotropic “elastic stiffness”, [Formula: see text], used in the HCA model. To calibrate the bulk modulus, K, the rate of pore pressure accumulation obtained from an undrained cyclic test and the rate of volumetric strain accumulation measured in a drained cyclic test are compared. Poisson’s ratio, ν, can be determined from the shape of the stress relaxation path measured in an undrained test with anisotropic consolidation stresses and strain cycles. Unfortunately, the calibration of K shown for a medium coarse sand in a previous paper by Wichtmann et al. in 2010 was affected by membrane penetration effects. Consequently, all further studies have been performed on a fine sand for which membrane penetration is negligible. The present paper reports on the new results. The strong pressure dependence of K and its independence from amplitude found in the previous study could be confirmed by the new tests. In addition, the new experimental results reveal a density dependence of K, while the bulk modulus is rather independent of stress ratio. Furthermore, for the first time Poisson’s ratio, ν, used in the HCA model has been calibrated based on tests performed with different amplitudes, densities, and initial stresses.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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 | 0.001 |
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".