Comparison of the measured and finite element–predicted ground deformations of a stiff lodgement till
Bibliographic record
Abstract
The use of the finite element method to model excavations and tunnels in Dublin black boulder clay has, in the past, had limited success owing to the failure of the available constitutive models in commercially available software programs to adequately represent the essential features of a stiff soil. A stiff soil — lodgement till — underlies much of the city of Dublin, Ireland; consequently, the successful prediction of deformations in this soil arising from structural and infrastructural projects is of considerable importance. Research has shown that the stress–strain response of a stiff soil is complex and depends on many factors including stress history, stress level, and strain direction. These important features are included in the hardening plasticity small strain stiffness (HSS) soil model that is incorporated in the Plaxis V8.4 finite element code. This paper describes the field and laboratory methods that were used to determine the parameters for incorporation in this soil model and the validation of these parameters. These parameters are used to model the deformations around two excavations: a 4.5 m deep excavation with a vertical face, and a 10.7 m deep excavation with a face slope of 70°–75°. Good agreement was found between the predicted and observed deformations.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| 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".