Replicating S-Shaped Composite Strength Response Using Bonded-Block Modelling: Capturing Dual Nature of Extensional Versus Shear Fracturing of Brittle Rock Mass
Bibliographic record
Abstract
ABSTRACT As mining operations pursue deeper and larger excavations, the accurate assessment of the risk of excessive rock deformations caused by brittle fracturing and dilation/bulking near excavation boundaries becomes increasingly important. To address this, the bonded-block modeling (BBM) approach such as UDEC-Voronoi has been widely used to simulate the complex brittle rock fracturing process and predict the shape of the excavation damage zone (EDZ) developed around underground openings. To realistically predict the EDZ shape, the BBM must be calibrated to accurately replicate the progressive failure of the brittle rock mass, characterized by a soften-hardening or composite S-shaped strength response. This can be achieved by specifying a number of input parameters based on fracture mechanics principles and a suitable calibration procedure. This approach allows for simulation of the in-situ brittle fracture processes. However, the available calibration methods are inadequate in capturing the dual nature of extensional versus shear fracturing of brittle rock masses due to their focus on laboratory sample fracturing behavior rather than large-scale rock response under in-situ stress paths. This paper provides practical recommendations for fine-tuning BBM input parameters from laboratory to field scales to reproduce observed failure mechanisms in-situ, advancing BBM as the state of practice for predicting overbreak formation in deep tunnels. The paper uses a hydroelectric tunnel in laminated sedimentary formations as a case study to calibrate the BBM model to the rock's S-shaped brittle strength. The calibrated micro-mechanical approach effectively captures the post-yield response of the rock mass, which is the key controlling mechanism in damage development around deep, lightly jointed grounds. The results demonstrate that for a realistic EDZ development and accurate capture of the mechanistic processes, BBM parameters must be calibrated to the long-term in-situ strength rock mass, rather than its short-term laboratory strength. The well-calibrated BBM model can be a practical and verified numerical tool for understanding and predicting damage formation around underground excavations.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 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".