Investigation of engineering-scale testing and bearing capacity calculation method for rotary screw special-shaped piles
Bibliographic record
Abstract
This paper investigates the bearing performance of rotary drilling screw special-shaped piles, a novel foundation solution designed to enhance load-bearing capacity in geotechnical engineering. Combining engineering-scale tests with numerical simulations, the study evaluates the interaction between piles and surrounding soil, with particular focus on the effect of thread geometry. The proposed orthogonal simulation model assesses the influence of key design parameters such as thread height, pitch, and pile length on compressive bearing capacity and end resistance. The results demonstrate that the thread structure increases the interaction area between the pile and soil, improving side friction resistance and overall bearing capacity. A method for calculating the bearing capacity of screw special-shaped piles is proposed, based on Meyerhof’s theory for deep foundations, which is validated through experimental data. This research provides valuable insights for optimizing pile foundation design and offers a reliable approach for calculating bearing capacity. The findings highlight the potential of screw special-shaped piles to enhance structural stability and material efficiency in challenging geotechnical conditions, offering a solid foundation for future studies on advanced pile systems in civil engineering.
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 | 0.002 |
| 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 | 0.001 | 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".