A general anisotropic yield function for <i>K</i><sub>0</sub>-consolidated clays
Bibliographic record
Abstract
The importance of yield surface for clays lies in describing compression behaviour, shear strength, and induced anisotropy. Various yield surfaces were proposed and adopted in modelling, but they are not consistent on describing anisotropic consolidation and/or undrained shear with both compression and extension stress paths of K0-consolidated clays. This study proposes a new generalized anisotropic yield function for K0-consolidated clays. First, limitations of existing yield surface are discussed based on comparisons with measurements of yield surfaces on various clays. Taking the more flexible isotropic yield function of Hardin and introducing the inclination angle of yield surface, a new generalized anisotropic yield surface is then proposed. The new anisotropic yield function is successfully examined on the predictive ability on the η-constant compression behaviour, and both the g( θ)-method and the TS-method (Transformed stress-method) can be adopted for taking into account the Lode angle effect in three-dimensional strength. Next, the new yield function is applied to develop an anisotropic elasto-plastic bounding surface model. The predictive performance is finally evaluated by comparing experimental and predicted results of anisotropic consolidation and shear tests on two reconstituted K0-consolidated clays.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".