Experimental study on penetration of bentonite grout through granular soils
Bibliographic record
Abstract
Permeation grouting using bentonite grouts is one of the effective methods to improve the engineering properties of granular soils. However, the low penetrability of bentonite grouts into soils limits their practical application in permeation grouting. This study presents a new approach to control the penetration length of bentonite grouts through granular soils using an ionic additive, sodium pyrophosphate (SPP). It is hypothesized that the chemical modification changes both rheological and physicochemical properties of the bentonite grout, and thus affects its penetration length through soils. The rheological properties (yield stress and apparent viscosity) of bentonite grouts with weight ratios (ratio of water to dry bentonite, W/B) of 19, 12.3, 9, and 7.3 were controlled by the addition of 1%–4% SPP by weight of dry bentonite. The bentonite grouts were also injected into sand columns prepared at various experimental conditions to evaluate the effect of each experimental parameter on their penetration lengths. The results show that the penetration length of bentonite grouts decreases with a decrease in W/B ratio and an increase in yield stress and apparent viscosity. Moreover, the penetration length increases with the increase of the normalized effective grain size and injection pressure, but the increase of fines content reduces the penetration length of the grouts. While the existing analytical equation produces good agreement with the measured penetration lengths for the grouts having high yield stress (>26 Pa), it significantly overestimates the penetration lengths of the SPP modified bentonite grouts due to filtration (especially, the grouts having low yield stress and low W/B ratios). Therefore, a new empirical correlation is proposed to predict the penetration length of the bentonite grouts based on filtration and rheological blocking.
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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".