A new versatile constitutive law for modelling the monotonic response of soft rocks and structured fine‐grained soils
Bibliographic record
Abstract
Summary This paper deals with a new critical state–based constitutive model for soft rocks and fine‐grained soils. The model, formulated in the single‐surface plasticity framework, is characterised by the following main features: (i) a generalised three‐invariant yield surface capable of reproducing a wide set of well‐known criteria, (ii) the dependency of the elastic stiffness on the current stress state by means of a hyperelastic formulation, (iii) the ability of simulating the plastic strain–driven structure degradation processes by a set of appropriate isotropic hardening laws, and (iv) a nonassociate flow rule in the meridian plane. The adopted formulation is hierarchical, such that the various features of the model can be activated or excluded depending on the specific kind of geomaterial to be modelled and on the quality and quantity of the related available experimental results. The constitutive model was implemented in a commercial finite element code by means of an explicit modified Euler scheme with automatic substepping and error control. The procedure does not require any form of stress correction to prevent drift from the yield surface. The performance of the model is first analysed by means of a wide set of parametric analyses, in order to highlight the main features and to evaluate the sensitivity of the formulation with reference to the input parameters. The model is then adopted to simulate the experimental response observed on three different geomaterials, ranging from soft clays to soft rocks.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".