Field investigation of steel screw micropiles under axial loads in cohesionless and cohesive soils
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Steel screw micropiles are a new pile type for light load applications or building remediation, offering several advantages over conventional concrete piles. Unique feature of screw micropile shafts requires distinctive design approaches; despite the growing use, there is limited field measured data on their axial failure or torque-based design. This study aims to evaluate the ultimate capacity of screw micropiles, analyze the axial failure mode, develop empirical correlations between installation torque and ultimate capacity, and refine a torque estimation method based on Cone Penetration Tests (CPT). Full-scale axial compression tests in both cohesionless and cohesive soils were performed on five screw micropile types with diameters ranging from 76 mm to 114 mm and lengths from 1.6 m to 3.0 m. Each test was repeated three times, totalling 30 tests. In-situ and laboratory investigations were conducted to characterize the soils. Results showed that in cohesionless soil, installation torque increased linearly with depth; while in cohesive soil, torque tended to stabilize after the threaded segment was fully embedded. The evidence suggests the impact of soil strength and disturbance on installation torque. A reliable linear relationship was observed between installation torque and ultimate capacities, with torque factors (defined as the ratio of pile ultimate capacity to max installation torque) ranging from 21.5 to 27.8 m −1 . Back-analysis suggested that the axial failure is governed by local bearing beneath each thread. The CPT-based torque estimation method in previous studies for piles in cohesive soil was revised to include the effect of smooth segment, and the revised method suggested consistent comparison with the measured torque.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it