3-D finite element analysis of laterally loaded short shafts in soil
Bibliographic record
Abstract
The objective of this research is to conduct an optimized design of drilled shaft foundation for noise barrier walls. A non-linear three-dimensional (3D) finite element method (FEM) program, Plaxis 3D, is used to investigate the behaviour of laterally loaded shafts. Two published cases are used to calibrate the modelling method and validate the numerical results. In the case of a field test performed by Helmers (1997), FEM results agree very well with field tests in terms of ultimate load and deflection curves. In the laboratory test conducted by Uncuoglu & Laman (2011) case, numerical results agree well with their results except the soil-shaft interface modelling part. The Plaxis 3D embedded pile model tends to overestimate the lateral load capacity of a smooth pile. Though it is satisfactory in modelling a pile with a “rough” surface. Two theoretical formulas in estimating lateral capacity of piles are also compared with the FEM results. It is found that Broms’s (1964b) theory for cohesionless soils has underestimated the lateral load capacities and Brinch-Hansen’s (1961) theory provides a more accurate estimation. In summary, 3-D FEM is able to accurately simulate the behaviour of laterally loaded drilled shafts in soil.
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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) | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".