Geotechnical capacity of hollow-bar micropiles in cohesive soils
Bibliographic record
Abstract
Hollow-bar micropile construction, also known as self-drilled, is becoming a popular option because it allows faster installation processes and ground improvement at the same time. This paper presents a field study and numerical investigation on the behaviour of single hollow-bar micropiles embedded in a stiff silty clay deposit. Four hollow-bar micropiles were installed using an air-flushing technique employing large drilling carbide bits. Five axial tests were conducted on the four micropiles, comprising three compression and two tension monotonic axial tests. The results of the field tests are presented and analyzed in terms of load–displacement curves. A two-dimensional axisymmetric finite element model (FEM) was created and calibrated using the field test results. The calibrated FEM was utilized to select an appropriate failure criterion for hollow-bar micropiles depending on the load-transfer mechanism of the micropiles. In addition, the model was employed to carry out a parametric study to investigate the effect of the installation methodology, hollow-bar micropile geometry, and shear strength of the surrounding soils on the micropile capacity. Based on the outcomes of the parametric study, an equation is proposed to estimate the axial capacity of hollow-bar micropiles in cohesive soils.
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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 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".