A simplified nonlinear approach for pile group settlement analysis in multilayered soils
Bibliographic record
Abstract
A simplified analytical method is presented for nonlinear analysis of the behaviour of pile groups under vertical loads. A hyperbolic approach is adopted to describe the nonlinear relationship between the shaft shear stresses and the relative shaft displacements along a confined disturbed soil zone around a pile-soil interface. Outside the disturbed zone, the soils are assumed to behave in a linearly elastic state. By adopting the elastic closed-form analytical solution to approximate the displacement fields around a single vertically loaded pile, and the principle of superposition, a new transfer function is presented for analysis of the behaviour of pile groups in multilayered soils. Furthermore, with a simplified assumption of separating the shaft from the base interaction factors for individual piles in a pile group, a highly effective iterative procedure is developed to examine the nonlinear loaddisplacement behaviour of a pile group up to the failure state. Comparisons of the loadsettlement responses for a number of well-instrumented field pile group test results are given to demonstrate the effectiveness and accuracy of the proposed analytical method. The computed nonlinear responses of the pile group compare favourably with measured field test results under both rigid and flexible pile cap conditions.Key words: pile groups, interface, transfer function, settlement analysis, nonlinear behaviour.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".