Formation of silica grout curtains and containments in mineralized groundwater
Bibliographic record
Abstract
An experimental investigation was conducted to evaluate the performance (as reflected by changes in permeability) of grouted soil specimens subjected to waters of various chemistry (mineralized groundwater) under a gradient of approximately 18. The specimens were composed of pure silica sand and clayey silty sand injected with one of two types of sodium silicate grout (sodium silicate + ethyl acetate-formamide, and sodium silicate + calcium chloride). The grouted specimens were tested in an environment that simulated different waters (distilled, freshwater, and saltwater). This work investigated the effects of curing time, environment, grout contents, and groundwater quality on the behaviour of silicate-grouted specimens, and analysed curtain formation mechanism. The test results showed that sodium silicate with ethyl acetate-formamide (SA) exhibited an increase in permeability when subjected to both freshwater and saltwater. Sodium silicate with calcium chloride (SC), however, maintained permeability properties when subjected to both freshwater and saltwater. The SC grouted specimens are less vulnerable to the action of groundwater than specimens grouted with SA. Furthermore, an empirical correlation relating the permeability of ungrouted and grouted specimens under different conditions was suggested. The correlation includes new defined parameters such as curing effect factor (α) and curtain vulnerability factor (κ).
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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 | 0.001 |
| 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 | 0.001 |
| 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".