A field study on the load sharing behavior of a micropiled raft underpinned by a waveform micropile
Bibliographic record
Abstract
A waveform micropile (WMP) uses the jet-grouting method to generate shear keys along the pile shaft for improving shaft resistance and cost efficiency. In this study, field loading tests were performed to characterize the load sharing behavior upon inclusion of a WMP in a group of four micropiles. First, single-pile compressive loading tests were conducted on three WMPs and five type A micropiles (MP). Subsequently, a group-pile loading test was performed on a piled raft comprising 2 × 2 MPs and a central WMP. The load–settlements, axial stiffnesses, and load transfer mechanisms of individual MPs were analyzed during the tests, including the short- and long-term effects of the axial stiffnesses of the MPs on the load sharing ratio of the micropiled raft. The single-pile loading test results revealed that the shear keys along the WMPs caused its bearing capacities and axial stiffnesses to be 1.5 times and 2–5 times higher than those of MPs, respectively. In the micropiled-raft loading test, the load sharing ratios of the MPs increased with their axial stiffnesses, and the highest load sharing capacity was exhibited by the WMP, which constituted 30% of the total load and 2–3 times that of MPs. Moreover, the influence of raft on the load-sharing capacity should be considered as well.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".