Evaluation of the Effects of Yielding Rockbolts on Controlling Self-Initiated Strainbursts: A Numerical Study
Bibliographic record
Abstract
In this paper, a 2D distinct element method (DEM) model of a deep tunnel in an underground coal mine is built to thoroughly evaluate the effects of yielding (D-bolt and Roofex) and the traditional rockbolt (fully resin-grouted rebar) on controlling self-initiated strainbursts. The occurrence of self-initiated strainbursts is judged based on the stiffness difference between the loading system and rock masses for the first time. The results suggest that the total deformations of the tunnel supported with Roofex and resin-grouted rebar are 1.53 and 2.09 times that of D-bolts (1411 mm). The average velocities of detached rock blocks in the tunnel supported with Roofex and resin-grouted rebar are 3.22 and 3.97 m/s, respectively, which are much higher than that of D-bolts (0.34 m/s). 13 resin-grouted rebar bolts are broken during the strainburst, while D-bolts and Roofex survive. Compared with Roofex (295.16 kJ) and resin-grouted rebar (125.19 kJ), the D-bolt can reduce the most kinetic energy (469.30 kJ). D-bolt and resin-grouted rebar can maintain high axial force levels (214.87 and 151.05 kN) during strainbursts. Both Roofex and resin-grouted rebar fail to control strainbursts. The bolt number significantly influences the control effects of yielding rockbolts on strainbursts. 9 and 12 D-bolts cannot control the strainburst, while 15 and 18 D-bolts can make the tunnel stable. In addition, the detachment and ejection of rocks between rockbolts can be well restrained using surface retain elements, e.g., steel arch. This study highlights the usage of numerical modeling methods in assessing the performance of yielding rockbolts, which can be served as a promising tool to improve and optimize the design of rock supporting in burst-prone 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 | 0.001 | 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".