Modelling the Behaviour and Efficiency of Minipile Groups in Clay
Bibliographic record
Abstract
Minipile groups have been used to create high load capacity foundations especially where significant space restrictions exist during construction. The interest in such foundations, particularly when the piles are arranged solely around a perimeter, initiated a research project in which geotechnical centrifuge model tests were used to investigate the key geometric parameters affecting the load-settlement behaviour and efficiency of groups of bored, slender, high aspect ratio piles. Circular and square perimeter pile groups were tested along with conventional grid groups. Two modes of failure were observed: either the individual piles pushed into the ground with no obvious settlement of the surrounding soil or as a block with the soil contained within the outer ring of piles settling by the same or similar amount as the piles. The change from block failure to individual pile failure generally occurred at a pile spacing of approximately 2 pile diameters. A complementary numerical modelling study gave insight into the pile-soil interaction and in particular the patterns of displacement as failure changed from individual pile to block mode. Overall, a grid group arrangement was found to be less efficient in terms of load carrying capacity than a perimeter group and the inclusion of a single target pile within a perimeter group could further enhance the group efficiency.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".