Dynamic behavior of pile foundations under vertical and lateral vibrations: review of existing codes and manuals
Bibliographic record
Abstract
Designing structures subjected to dynamic loads is quite complex and involve structural, mechanical, geotechnical engineering and the theory of vibration. Machines, buildings under seismic effect, and wind turbines induce both dynamic and static loads on their foundations. If these structures are supported on piles, a full understanding is required of the dynamic interaction between individual piles and soil (pile-soil interaction) and between adjacent piles (pile-soil-pile interaction). Due to the complexity of this problem, codes and manuals recommend the use of approximate approaches. However, there is a general lack in research concerning the accuracy of these approaches. The present paper aims to help filling this gap by comparing the recommendations from selected codes and manuals with the results obtained from the numerical analysis. The codes and manuals considered in this paper are the Egyptian Code (EC), ACI, and the Canadian Manual (CM). This comparison is held over a range of parameters including excitation force frequency (f), soil modulus of elasticity (Es), pile slenderness Ratio (L/D), dimensionless spacing ratio (S/D) and pile group size (ng). At the end of this study, advantageous and downfalls of these approaches are discussed.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".