Residual shear strength of fine-grained soils and soil–solid interfaces at low effective normal stresses
Bibliographic record
Abstract
A laboratory research program was undertaken to study the large-strain shear strength characteristics of fine-grained soils under low effective normal stresses (∼3–7 kPa). Soils that cover a wide range of plasticity and composition were utilized in the program. The interface shear strength of these soils against a number of solid surfaces having different roughness was also investigated at similar low effective normal stress levels. The findings contribute to advancing the knowledge of the parameters needed for the design of pipelines placed on sea beds and the stability analysis of shallow soil slopes. A Bromhead-type torsional ring-shear apparatus was modified to suit measuring soil–soil and soil–solid interface residual shear strengths at the low effective normal stresses. In consideration of increasing the accuracy of assessment and depicting the full-scale field behavior, the interface residual shear strengths were also measured using a macroscale interface direct shear device with a plan interface shear area of ∼3.0 m2. Correlations are developed to estimate the soil–soil and soil–solid interface residual shear strengths at low effective normal stresses. The correlations are compared with soil–soil and soil–solid interface drained residual shear strengths and correlations presented in the literature.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".