Modeling the stress versus settlement behavior of shallow foundations in unsaturated cohesive soils extending the modified total stress approach
Bibliographic record
Abstract
The mechanical behavior of unsaturated soils can be interpreted using either modified total stress or a modified effective stress approach depending on the type of soils and various scenarios of drainage conditions of pore-water and pore-air. Recent studies suggest that the bearing capacity of unsaturated cohesive soils can be more reliably estimated using the modified total stress approach (MTSA) rather than the modified effective stress approach (MESA). In the present study, a modeling technique (extending Finite Element Analysis, FEA) is proposed to estimate the bearing capacity of shallow foundations in unsaturated cohesive soils by simulating the vertical stress versus surface settlement behaviors of shallow foundations extending the MTSA. The proposed technique is verified with the model footing test results in unsaturated cohesive soils. Commercial finite element software, SIGMA/W (GeoStudio 2012, Geo-Slope Int. Ltd.) is used for this study. Details of estimating the unsaturated soil parameters (i.e. total cohesion, modulus of elasticity and Poisson’s ratio) required for the FEA are also presented taking account of the influence of matric suction. Good agreements were observed between the measured bearing capacity values and those from the FEA extending the MTSA.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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".