Bibliographic record
Abstract
A rigorous analytical method is developed for calculating the interaction factor between two identical piles subjected to vertical loads. Following the scheme proposed by Muki and Sternberg, the problem is formulated by decomposing the pile soil system into an extended soil mass and two fictitious piles. With the consideration of the compatibility condition that the axial strain of the fictitious pile be equal to the corresponding strain average over the extended soil, a Fredholm integral equation of the second kind governing the unknown axial forces along fictitious piles is established and then solved using numerical procedures. The real pile head settlement is subsequently calculated based on the determined fictitious pile forces and finally, the desired pile interaction factor is derived. Comparison with existing solutions confirms that the conventional interaction factor approach does tend to overestimate the interaction and may cause considerable errors for long compressible piles. Numerical results for the interaction factor between two piles in both semi-infinite and finite layered soils are presented over a wide range of pile and soil parameters, and also the settlement behaviour of a 3 × 3 pile group embedded in a semi-infinite soil is studied by virtue of the newly established interaction factor.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".