Drag Load on Piles in Partially Saturated Collapsible Soils
Bibliographic record
Abstract
Collapsible soils possess a considerable strength when dry, and experience a significant and sudden loss in its strength and excessive settlement upon wetting. In the field, wetting may take place due to the rise of the groundwater level or flooding on the ground surface. End-bearing piles are widely used to penetrate these collapsible layers, in order to transfer the building load to a stronger deeper soil layer. While in the literature, reports can be found dealing with evaluating the interaction between piles and collapsible soil when fully inundated (full saturation), the research on the behavior of this soil when partially saturated is lagging behind. This is due to the complexity of modeling and the lack of field data. This paper presents the results of experimental modeling of an end-bearing pile penetrating collapsible soil subjected to partial inundation due to surface running water. The objective is to determine the drag load acting on the pile’s shaft when the degree of saturation increases along the collapsible soil layer surrounding the pile shaft. The measured drag load is presented as function of the degree of saturation, the collapse potential of the soil layer and pressure acting on the soil.
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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".