Optimization of strength and homogeneity of deep mixing material by the determination of workability limit and optimum water content
Bibliographic record
Abstract
With ongoing development of the “deep mixing method”, the scope of applications is always widening. Once confined to ground improvement applications (i.e., to ensure stability and reduce settlements of structures on soft soils), use of this method now ranges from cut-off walls to structural elements and retaining walls. Indeed, the execution is easier, with limited excavated material, and costs less than traditional methods. With these new applications, the required hydraulic and mechanical properties of the soil-mixing material have also evolved, and numerous investigations on the hardened material have been carried out. However, properties of the material in a fresh state must be studied too, and particularly its workability because it is essential for continuity and homogeneity purposes. A laboratory program was carried out to determine the workability evolution of the material with increase of cement content. Results show that the material’s workability limit varies greatly with cement content, and that at constant dosage the clay content still controls the evolution of the material liquid limit. Also, this paper shows a method to determine the optimum water content for the deep mixing material, meaning that instructions can be given on site to ensure that optimum mechanical characteristics are reached.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".