Numerical modeling of rock spalling around a tunnel using visco-plastic interface elements and a rock removal strategy
Bibliographic record
Abstract
Rock spalling is a brittle failure process that occurs around tunnels excavated in hard rock under high in-situ stress states. In nuclear waste disposal, spalling in fractured crystalline rock could create connected fractures, potentially providing pathways for radionuclides. Robust numerical models are therefore needed to evaluate the extent of rock spalling so that the design and layout of a prospective deep geological repository can be optimized and made fit for purpose. With this motivation in mind, this study proposes a methodology for the numerical analysis of rock spalling based on zero-thickness interface elements with a visco-plastic-fracture constitutive law, combined with a workflow for finite element removal/excavation. To simulate spalling, zero-thickness interface elements are pre-inserted along a sufficient number of mesh lines with random orientation within the rock mass. A uniform initial stress state is generated and the excavation of the circular tunnel is performed by removing the corresponding elements, which leads to stresses in excess of the elastic limit in some of the interfaces, and subsequent visco-plastic fracture openings. A criterion for excavation of the finite elements around the tunnel is established when a block which is totally surrounded by failed interfaces is totally detached or can slide off the mesh following a kinematically admissible path. The excavation of blocks causes a stress redistribution around the tunnel and this leads the need for new excavation steps, until a new equilibrium configuration is reached. The proposed methodology is applied to assess rock spalling in the Mine-by Experiment at the Atomic Energy of Canada Limited’s (AECL’s) Underground Research Laboratory in the massive Lac du Bonnet granite. The focus of the analysis is to understand the mechanisms and the influencing factors that lead to brittle failure, and to calibrate material properties to reproduce both the final stress state of the tunnel and its spalling depth.
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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 | 0.000 |
| 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".