Requirements of efficient deep soil mixing treatment in clayey soils: a field-based assessment of water predrilling and auger free blade effects
Bibliographic record
Abstract
Achieving a uniform/high-strength deep soil mixed (DSM) column and avoiding sticking cohesive soils to blades (i.e., entrained mixing/rotation phenomenon) requires multi-disciplinary involvement, including drilling tool configuration and mix designs. A series of 80 cm diameter DSM columns was executed in high cohesive clays using various drilling auger formations containing different numbers of free blades and with/without water predrilling phases. Data interpretation was combined with full-depth coring and rig sensor records. The outcomes highlighted that adding free blades to the auger in a proper formation (dimensions/placement/shape/stiffness) resulted in uniform columns and facilitated the drilling by reducing the drilling pressure by about 40% while all the parameters were the same. The required water discharge in the predrilling phase was formulated to aim for a water content (about 46%) beyond the liquid limit of clayey deposits (21%–44%): a decisive technique to facilitate drilling in stiff cohesive soils. A 100% increase in the strength and a 50% enhancement in uniformity indexes in the executed columns of this project were achieved only through a tuned free-blade auger (number/configuration) and an optimal amount of added water. Besides, simultaneously implementing the predrilling phase and free blades to maximize drilling quality was inevitable due to their intertwined functions. Moreover, a new practical equation has also been proposed to consider the effect of free blades on the BRN within cohesive soil layers.
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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".