Effects of screw pile installation on installation requirements and in-service performance using the discrete element method
Bibliographic record
Abstract
Existing guidance on the installation of screw piles suggest that they should be installed in a pitch-matched manner to avoid disturbance to the soil that may have a detrimental effect on the in-service performance of the pile. Recent insights from centrifuge modelling have shown that installing screw piles in this way requires large vertical compressive (or crowd) forces, which is inconsistent with the common assumption that screw piles pull themselves into the ground requiring minimal vertical compressive force. In this paper, through the use of the discrete element method (DEM), the effects of advancement ratio, i.e., the ratio between the vertical displacement per rotation to the geometric pitch of the helix of the screw pile helix, on the installation resistance and in-service capacity of a screw pile is investigated. The findings are further used to assess the applicability of empirical torque capacity correlation factors for large diameter screw piles. The results of the investigation show that it is possible to reduce the required vertical compressive installation force by 96% by reducing the advancement ratio and that although over-flighting a screw pile can decrease the subsequent compressive capacity, it appears to increase the tensile capacity significantly.
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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 | 0.003 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".