Optimising deep mixed soil zones in land reclamation projects
Bibliographic record
Abstract
The use of deep soil mixing technologies has become increasingly common in North America following its widespread development and adoption in Japan and Scandinavia. This research project considered how design of soft soils stabilised with deep soil mixing may be optimised to satisfy global slope stability requirements to assist the construction of large reclaimed land projects. The land reclamation case that was studied in the present paper deals with raising the elevation of a terrestrial area above a tidal or flood zone, where the water table is close or at the original grade. In this work, the effect of several key design parameters on the global factor of safety against slope failure for a land reclamation project was studied using limit equilibrium slope stability analyses. The parametric analyses considered design parameters, including the thickness of the soft soil layer, as well as the strength, width and location of a stabilised soil zone. The purpose of this work is to provide guidelines for the preliminary design of ground improvements for future land reclamation projects using deep soil mixing methods by identifying design parameters that have the most significant impact on the global factor of safety.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".