Improved Methods of Design for Grouting Fractured Rock
Bibliographic record
Abstract
The effectiveness of grouting fractured rock depends on the distance that grout penetrates into individual fractures and spreads into connected fracture networks. Assessing grout spread, and the consequent effect on groundwater flow, requires consideration of the 3-D geometry and hydraulic properties of the natural fracture network. Discrete fracture network (DFN) modeling, conditioned to site characterization data, suggests grouting is most effective if the volume injected is based on that stage's fracture aperture: Aperture Controlled Grouting (ACG). The ACG procedure differs from the familiar GIN procedure in that: i) grout take is now a requirement to be met based on stage Lugeon value, not an outcome that depends on the mixture of grout rheology and injection pressure; and, ii) grout mix is now varied, depending on ground response, to achieve the required pressure build. This paper discusses the basis of ACG grouting; a companion paper at this conference (Bonin et al. 2012) presents the field procedures.
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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 | 0.001 | 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".