Group reduction factors for analysis of laterally loaded pile groups
Bibliographic record
Abstract
The lateral response of piles embedded in soil is typically analyzed using the beam on nonlinear Winkler springs approach, in which soil–pile interaction is modeled by nonlinear p–y curves (where p is soil resistance and y is horizontal displacement). In this approach, one of the most common methods of accounting for interaction effects in pile groups is to modify the single pile p–y curves using a p-multiplier for each row of piles in the group, with higher values for leading row and lower values for trailing rows. The leading and trailing rows interchange during seismic loading; therefore, sometimes an average p-multiplier is used for all piles in the group. This average p-multiplier is called the group reduction factor. Group reduction factors have been established from experimental data from static loading tests on small pile groups, mostly 3 × 3 groups with free pile head conditions and center-to-center pile spacings of about 3 pile diameters. In this paper, continuum simulations are used to study the group reduction factors in 3 × 3 to 6 × 6 square pile groups subjected to static loading. The study includes the effects of various parameters, including pile spacing, pile head condition, and the friction angle of soil, on the group reduction factors. Calculated group reduction factors from this study compare well with available group test data, that is, typically small pile groups. However, the study shows that design guidelines such as the American Association of State Highway and Transportation Officials (AASHTO) and Federal Emergency Management Agency (FEMA) P-751 overestimate the group reduction factors, hence the lateral resistance, in larger pile groups and larger spacings, especially for fixed pile head conditions.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 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".