On the “elastic” stiffness in a high-cycle accumulation model for sand: a comparison of drained and undrained cyclic triaxial tests
Bibliographic record
Abstract
High-cycle accumulation (HCA) models may be used for the prediction of settlements or stress relaxation in soils due to a large number of cycles (N > 103) with a relatively small-strain amplitude (εampl < 10−3). This paper presents a discussion of the elastic stiffness, [Formula: see text], used in the basic constitutive equation of an HCA model, [Formula: see text], where [Formula: see text] is the trend of effective stress, [Formula: see text] is the trend of strain, [Formula: see text] is the rate of strain accumulation, and [Formula: see text] is the plastic strain rate. [Formula: see text] interrelates the “trends” of stress and strain evolution. For the experimental assessment of the bulk modulus, [Formula: see text], the rate of pore-water pressure accumulation, [Formula: see text], in undrained cyclic triaxial tests and the rate of volumetric strain accumulation, [Formula: see text], in drained cyclic tests have been compared. The pressure-dependent bulk modulus, K, was quantified from 15 pairs of drained and undrained tests with different consolidation pressures and stress amplitudes. It is demonstrated that both the curves [Formula: see text] in the drained tests and u(N) in the undrained tests are well predicted by the authors’ HCA model if the elastic stiffness is determined using the method described in the present paper. A simplified determination of K from the unloading and reloading curve in an oedometric compression test is discussed.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 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".