Physical and numerical models of pressure during waterproofing injections with polymer into concrete fractures
Bibliographic record
Abstract
Polymer injections in concrete fractures are commonly used for the waterproofing of tunnels. The pressure during the injection needs to be high enough to ensure polymer penetrability. This paper introduces two physical models for the study of the pressure inside concrete fractures during polymer injections. The injection parameters that were varied include pressure, injection duration, injection volume, location of the injection and pressure reading ports, and fluid dynamic viscosity. Water and water-glycerol mixtures were used to verify the influence of viscosity on flow. Tests were performed with both open and sealed fractures. The pressure inside the fracture during the injection was influenced by the dynamic viscosity, boundary conditions and the saturation level of the fracture. Sealed and initially moist fractures led to a higher pressure gain inside the fracture after achieving saturation. More than 40% of the injection pressure was already lost when the liquid entered the model. A numerical model of liquid flow in the fracture plane was developed with the finite element code COMSOL Multiphysics. It was able to replicate the influence of boundary conditions and initial fracture saturation on pressure. The model also shows how aperture and roughness influence the flow conditions in the fracture.
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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 | 0.001 |
| 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".