Axial performance of micropile groups in cohesionless soil from full-scale tests
Bibliographic record
Abstract
Hollow bar micropile (HBMP) groups are used for supporting large loads as an alternative foundation option to large diameter drilled shafts. In such cases, it may be necessary to increase the micropile’s diameter by increasing the drill bit diameter (D b ). This paper investigates experimentally and numerically the effect of increasing D b and micropile spacing on the group performance. A field load testing program was conducted on four groups of HBMPs installed in sand; each group comprised four micropiles arranged in a square configuration. All micropiles were constructed with the same size hollow bar, D h = 51 mm; two groups comprised micropiles constructed with drill bit, D b = 115 mm, and two groups comprised micropiles constructed with drill bit, D b = 152 mm. One group of each set was installed with spacing to micropile diameter ratio, S/D b = 3 and the other group with S/D b = 5. In addition, full 3D finite element model (FEM) was developed and calibrated to simulate the behaviour of micropile groups and to evaluate the failure load for groups that were not loaded to failure. The results demonstrated that micropile groups constructed with the large diameter drill bits displayed higher stiffness and load carrying capacity than the groups constructed with small diameter bits, which confirms the effectiveness of using a larger drill bit. In addition, the group efficiency ratio values at both working load and ultimate capacity were found to be close to unity for all groups. The ultimate skin friction values of grouted micropiles obtained from this study were higher than the values suggested by the US Federal Highway Administration for medium to very dense sand. It was also found that the settlement of the 4-HBMP group increased by 25% to 33% over that of a single HBMP due to group effect.
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How this classification was reachedexpand
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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".