Numerical modeling of sand drain performance — a case study of the Salter Street Bridge construction
Bibliographic record
Abstract
Several bridge crossings proposed for the Red River Floodway expansion project were recently constructed using vertical sand drains to accelerate excess pore-water pressure dissipation and settlement caused by embankment fill loading. With limited local data regarding the performance of sand drains, the calibrated model presented here addresses the need to optimize the design of sand drain configurations, maximize cost savings, and minimize construction delays for future structures. This study presents a coupled finite element embankment consolidation model calibrated against measured pore-water pressure and settlement data from the Salter Street Bridge embankment fill construction, which used vertical sand drains to dissipate excess pore-water pressures. A hydraulic conductivity modification procedure was used to simulate the axisymmetric flow conditions with a plane-strain model neglecting well resistance but incorporating the effects of a smear zone. A sensitivity analysis was performed using the calibrated model by varying the smear zone radius and hydraulic conductivity and the undisturbed soil hydraulic conductivity. The sensitivity analysis predicted that the observed behaviour was predominantly sensitive to the hydraulic conductivity of the smear zone and the surrounding 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 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".