Goa, India FRACOD Modeling of Rock Fracturing and Permeability Change in Excavation Damaged Zones
Bibliographic record
Abstract
ABSTRACT: Characterization of Excavation Damaged Zone (EDZ) around an underground excavation is a major research topic for deep geological disposal of medium to high level radioactive waste. Rock fracturing due to excavation and thermal loading and its resultant rock mass permeability change in the EDZ are important aspects in the EDZ characterisation. A new function to predict rock mass permeability change in fractured rocks has been developed and added into the existing fracture mechanics code FRACOD. The new functions in FRACOD has been applied to predict the extent of EDZ and permeability change in the vicinity of the TSX tunnel of URL (Canada), the ZEDEX tunnel of the Äspö Hard Rock Laboratory (Sweden) and the deposition tunnels in crystalline and sedimentary rocks (Japan). The predicted the EDZ and its permeability are consistent with the measurement data of the TSX tunnel. In the validation test against the ZEDEX tunnel results, a broad agreement between the FRACOD prediction and measurements has been achieved. The results from both tests indicate that FRACOD with the new function is capable of realistically predicting the EDZ and permeability change. Following the validation tests FRACOD is applied to studying the EDZ of conceptual deposition tunnels for radioactive waste in Japan. 1
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".