Techniques for Progressive Failure Simulation of Hard Brittle Surrounding Rockmass: Taking the URL Test Tunnel as an Example
Bibliographic record
Abstract
Accurate simulation of the failure process of hard brittle surrounding rockmass is very important for the analysis and control of the structural stability in deep underground engineering. In order to simulate the progressive failure process of the hard brittle surrounding rockmass, a continuous discontinuous deformation analysis method that couples the finite element and discrete element is adopted. Taking the URL test tunnel in Canada as an engineering case, the constitutive model of the contact considering the effects of cohesion weakening and friction strengthening is applied, and the 2D approximation to 3D excavation by applying elastic modulus reduction technology is adopted to simulate the range and depth of crack growth of the surrounding rockmass. Then, the comparison between simulated results and on‐site monitoring results is performed, which shows good consistency. At the same time, the key factors in the numerical simulation of progressive failure in hard brittle rockmass are identified, including the number of elements, excavation effects, and constitutive models. The results show that the constitutive model determines the basic form of crack propagation, but in order to accurately simulate the progressive propagation of cracks, the number of elements must be sufficient enough and the effects of 3D excavation must be considered. The analysis accurately simulates the progressive failure characteristics of hard brittle surrounding rockmass under high stress, achieving the purpose of reasonably grasping the degree of damage to the surrounding rockmass, and provides technical reference and support on how to accurately simulate the failure of hard brittle surrounding rockmass using the finite discrete element method.
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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 | 0.001 |
| 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".