Centrifuge study on the uplift behavior of spread foundation for transmission tower in sand
Bibliographic record
Abstract
Realistic simulation of in-situ stresses is an essential consideration in evaluating the bearing capacities of spread foundations. Therefore, this study aimed to investigate the uplift behavior of large spread foundations by performing a series of centrifuge tests. A total of 12 centrifuge test models were constructed considering the variation in the foundation width (3.5–6.5 m), embedment depth ratio (0.67–1.39), and relative density of dry silica sandy soil (40%, 80%). The measured load–displacement curves indicated that the uplift bearing capacity and the corresponding uplift displacement increased with the foundation width at a certain embedment depth ratio. Two sets of empirical equations were proposed by adopting genetic programming to estimate the uplift resistance factor and uplift displacement with consideration of field stress conditions. The proposed equations reasonably matched these parameters under various conditions reported in the literature. Furthermore, a simplified empirical influence zone was proposed on the basis of the measurement of the ground surface displacement. The empirical influence zone, which was a straight line with an inclination angle of ~0.9 times the soil friction angle measured from vertical, could be considered a significant reference for predicting the failure surface of the shallow foundation under uplift loading.
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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 | 0.000 | 0.001 |
| 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 | 0.000 |
| 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".