Research on slurry mix ratio of sleeve valve pipe grouting for subway and its engineering application
Bibliographic record
Abstract
Sleeve valve pipe grouting plugging is the most commonly and effective method to control water leakage of subway station. The success of plugging grouting depends largely on performance indicators of grouting materials such as fluidity, setting time, and slurry stone strength. In this paper, a series of experiments were carried out to study the regulation of initial setting time, final setting time, viscosity, bleeding rate, compressive strength of cement–water glass slurry under different mix ratios. Based on the analysis of the results, combined with hydrogeologic condition of Furong East Road Station of Xi'an Metro, the optimal slurry mix ratio is 0.6 water–cement ratio and 1% water glass content. The field grouting test and numerical simulation show that the cement–water glass slurry grouting with this ratio has good grouting and waterproofing effect. The research results have great guiding significance for the water leakage treatment in subway stations.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| 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".