Pore-pressure coefficients for unsaturated soils: generalized effective stress approach
Bibliographic record
Abstract
Geotechnical problems with total stress changes occurring rapidly relative to the soil consolidation time can be conveniently addressed using an effective stress-based approach. For saturated states, analytical formulations of pore-pressure coefficients adopting coherent effective stress concepts exist. These formulations allow the induced pore water pressure variations and the corresponding effective stress changes to be determined. For unsaturated states, there are no analytical formulations of pore-pressure coefficients that adopt a suitable effective stress concept. This paper presents analytical derivations of pore-pressure coefficients for unsaturated elastic isotropic soils using the generalized effective stress (valid for saturated and unsaturated states) for different total stress changes. The model performance is described, and flowcharts to be adopted in engineering practice are provided. Compared with an existing approach that is not based on the effective stress, the proposed one requires fewer constitutive parameters (one of which, conveniently, is the soil bulk modulus), allows to analytically obtain the existing expressions for saturated states when the degree of saturation is 1 and to readily determine the retention curve under undrained conditions. Existing experimental data were analysed, and satisfactory interpretations and predictions of the experimental results were obtained. The proposed framework is a valuable tool for undrained mechanical analyses of unsaturated soils under different practical applications.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 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".