Adaptation and Validation of the Small Strain Hardening Soil Model for Sensitive Clays in Eastern Canada
Bibliographic record
Abstract
Abstract This study focuses on the modelling of the complex behaviour of Champlain Sea deposits of Éastern Canada. Sensitive clays present unique geotechnical challenges due to their significant strength loss upon remolding and complex stress-strain response. The research was conducted in two phases: (1) a laboratory investigation of Louiseville clay under various stress paths and (2) the development and validation of a modified constitutive model based on the Hardening Soil model with small-strain stiffness (HSsmall). Standard HSsmall showed limitations in representing the behaviour of structured sensitive clays, especially in the overconsolidated range. To address this, the HSSstruct model, which improves upon HSsmall by eliminating pre-failure shear hardening, was developed. Validation against laboratory tests showed excellent agreement, with an average deviation of ±2 kPa in undrained shear strength predictions, along with accurate pore pressure response and strain at failure under various stress paths. The model effectively captured the quasi-elastic behaviour of structured sensitive clays before peak strength and outperformed the traditional Mohr-Coulomb model. Despite the need for further refinements for cyclic loading and post-peak softening, this represents the first dedicated constitutive model for Éastern Canadian sensitive clays. Its integration into Plaxis enables advanced elasto-plastic modelling, improving the reliability of geotechnical design in sensitive clay regions.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.002 | 0.001 |
| 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".