Modification of Sands Using <i>N</i> -Sodium Silicate Grout: Impact of Permeation versus Gelation Times
Bibliographic record
Abstract
Grouting is a method used regularly to alter in situ engineering soil properties, mainly strength, stiffness, and permeability. Chemical grouting constitutes injection of one or more fluids in grouting holes, with the aim of permeating the desired volume before the grout gels. Engineers require vital parameters during pre-gelation and post-gelation to quantify the economics and the efficiency of the treatment. The field of chemical grouting is highly contingent on laboratory and field pilot experiments, due to the convolution of its mechanisms and processes. This study aims at understanding the performance of Ottawa sand grouted using a commercial N-sodium silicate grout neutralized by dibasic ester. Particularly, this research seeks to investigate the impact of the gelation time, relative to grout permeation time, on the strength of the grouted sand. After studying, the rheology and syneresis of various mixes, candidate mixes were selected and permeated through 6-in. sand columns. Unconfined compressive strength tests were then performed on the specimens after their extraction to characterize the effect of sedimentation and filtration mechanisms during and post grouting (but prior to gelling). Two grouts with different gelation times were used in this study (20 and 30 min), and the specimens were permeated with different number of pore volumes (1–9). The permeation process was initiated either right after mixing or after a delay such that the permeation is concluded at the onset of gelation. The compressive strength increased with increasing number of pore volumes permeated; additionally, specimens with delayed permeation yielded higher strengths and stiffnesses than those permeated without a delay at a similar grout intake.
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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 | 0.000 |
| 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) | 0.001 | 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".