Use of 3DEC to study spalling and deformation associated with tunnelling at depth
Bibliographic record
Abstract
For mining at depth or deep caving operations, it is increasingly important to better understand the failure process near underground excavations and, for support design, it is necessary to better anticipate the related deformation characteristics of brittle failing rock. This paper describes how 3DEC was used to model the rock mass as an assembly of tetrahedral (tet) blocks bonded at their contacts, and to investigate spalling and unidirectional bulking of massive to moderately jointed rock masses by introducing tensile strength heterogeneity at the block contacts. The 3DEC approach differs from particle-based methods in its ability to represent a zero-initial porosity condition, as well as interlocked irregular block-shapes that provide resistance to block rotation (moments) after contact breakage. These processes tend to dominate the rock mass behaviour in low confinement zones near excavations and thus are relevant for both stability assessment and support design. The results of simulations employing this approach are summarised to assist in understanding the growth of fracture patterns and related stress redistribution, as well as deformation around a highly stressed tunnel. Mining-induced stress changes are approximated to simulate the effects of over-mining with an undercut, as typically used in a cave mine. The model response is found to be consistent with current theories concerning the spalling and bulking of massive rock at depth and with observations made in analogous civil and mining tunnels. However, the results also suggest that data from continuum models with plasticity models may be misleading in terms of extent and deformation in the non-elastic zone. This paper supports the view that excavation stability in brittle rock types is dominated by tensile or extensional failure processes near the excavation and that bulking enhanced by geometric block-shape factors needs to be considered for support design.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".