Axial Compression and Uplift Performance of Continuous Helix Screw Piles
Bibliographic record
Abstract
This study investigates the axial performance of continuous helix screw piles compared to helical piles through full-scale compression and tension load testing in layered soils. Twenty-three piles were installed and tested. The results demonstrate that screw piles can achieve considerable axial capacity with lower installation torque than helical piles, particularly under tensile loading. The capacity-torque relationship for screw piles was more consistent across both compression and tension, likely due to reduced soil disturbance from the smaller helix projection. Strain gauge measurements indicated that screw piles act primarily as friction piles with the threaded shaft carrying most of the load, especially in stiff clay. On the other hand, the smooth portion of the pile shaft contributed only marginally to resistance in compression and none in tension. The calculated capacity based on theoretical equations aligned well with field results in compression, with screw piles best represented by cylindrical shear failure in sand and a combination of cylindrical shear and individual bearing failure in clay. However, there is greater variability between calculated and measured uplift capacity, possibly due to soil disturbance effects. Additionally, the commonly used helix spacing ratio (S/D) was found to be less applicable to screw piles in predicting failure mode due to their smaller shaft-to-helix diameter difference.
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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) | 0.001 | 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".