Experimental investigation and constitutive modeling of the behaviour of highly plastic Lower Rhine clay under monotonic and cyclic loading
Bibliographic record
Abstract
A new experimental series on the highly plastic (plasticity index, IP = 34%) Lower Rhine clay (LRC) is presented. The study comprises tests on normally as well as overconsolidated samples under monotonic and cyclic loading. The loading velocity has been varied to evaluate the strain rate dependency of the LRC behaviour, testifying the well-known reduction of undrained shear strength with decreasing displacement rate. Isotropic consolidation followed by a cyclic loading with constant deviatoric stress amplitude leads to a failure due to large strain amplitudes with eight-shaped effective stress paths in the final phase of the tests. The inherent anisotropy has been additionally evaluated using samples cut out in either the vertical or the horizontal direction. Furthermore, the behaviour of LRC is compared with the behaviour of low plastic kaolin silt (IP = 12.2%). A new visco-hypoplastic-type constitutive model with a historiotropic yield surface has been used to simulate some of the experiments with cyclic loading. Even the eight-shaped stress loops at cyclic mobility are reproduced well with this model. The data of this paper can be also used by other researchers for the examination, calibration, improvement, or development of constitutive models dedicated to fine-grained soils under monotonic and cyclic loading.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".