New method to determine proper strain rate for constant rate-of-strain consolidation tests
Bibliographic record
Abstract
The development of a new semiempirical method to predict the proper strain rate for constant rate-of-strain (CRS) consolidation tests is described herein. The validity of the proposed method is analyzed using experimental results from CRS and incremental loading tests on four types of soil: Lake Bonneville clay, Massena clay, kaolinite, and montmorillonite. It is found that the maximum allowable strain rate depends on the initial void ratio of the soil and thus is related to the compressibility of the soil. The effect of the strain rate on the distribution of the pore pressure within the sample is investigated by comparing values of effective vertical stress calculated using a linear equation published by Wissa et al. in 1971 with values of effective stress at the base of the specimen determined from measured values of pore pressure. Overall, the proposed method predicts the maximum allowable strain rate very well for three of the four soils and moderately well for the other soil.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".