Bibliographic record
Abstract
Geological structures such as faults, joints, and dykes have been observed near excavation boundaries in many rockburst case histories. In this paper, the role of weak planes around tunnels in rockburst occurrence was studied. An Abaqus explicit code was used to simulate dynamic rock failure in deep tunnels. Firstly, Abaqus’s usefulness for modeling geomaterials was improved by introducing material heterogeneity using Python scripting. Modeling results showed that heterogeneous models resulted in more realistic failure modes than homogeneous models. Secondly, rock failure near the excavation boundary of a tunnel without any adjacent geological structure was modeled and released kinetic energy from rock due to failure and velocity of elements at the tunnel wall were calculated. Then, a weak plane was added to the model. This resulted in more released kinetic energy and higher element velocity, indicating that rock failure became more violent in the models with weak planes. The modeling results confirm that the presence of geological structures in the vicinity of deep excavations is a condition for the occurrence of rockburst. It explains localized rockburst occurrence in civil tunnels and mining drifts. The presented methodology in this paper for rockburst analysis can be useful for rockburst anticipation and control during mining and tunneling in highly stressed grounds.
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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".