Utilizing Coseismic Strain in the Modelling of Tunnel Loading in Deep Burst-Prone Mines
Bibliographic record
Abstract
ABSTRACT: Seismic monitoring data acquired at mines can be used to infer the characteristics of coseismic strain, including amount, orientation of principal directions and type (deviatoric, volumetric explosive or implosive). This strain corresponds to plastic strain increment if seismic events represent episodes of sudden deformation in confined environment. If sources of seismic events involve the convergence of excavations, then coseismic strain depends on the amount of the convergence. These peculiarities of coseismic strain are taken into account in the proposed method for its direct incorporation into a numerical stress model. The method is verified using analytical cases of confined inelastic deformation as well as brittle failure around a tunnel. The method can be used to assess the redistribution of stresses and change in the loading of tunnels in seismically active mines. A synthetic mining example is presented to illustrate the impact on tunnel stress. 1 INTRODUCTION Seismic systems installed at mines record seismic waves radiated by episodes of sudden (i.e., durations on the order of fractions of a second) deformation within the rockmass. The analysis of these recorded waves make it possible to assess the time, location, amount and intensity of deformation, as well as its geometrical characteristics (e.g., direction of principal strains, proportion of volumetric and deviatoric shape change). This information is highly valuable for understanding the overall rockmass deformation induced by mining and the associated redistribution of stresses. It is quite logical that the characteristics of rockmass deformation inferred from seismic data are often utilized when performing numerical stress modelling. There are fundamentally two ways to do this. Firstly, seismic data can help to improve the input parameters of the stress models. This is often done through qualitative or quantitative comparing of various aspects of seismic data (e.g., location of sources) with the corresponding modelling parameters (e.g., areas of high deviatoric stress) – see, for example, the works of Lachenicht (2001); Beck and Brady (2002); Beck et al. (2006); Spottiswoode et al. (2008); O'Connor et al. (2010); Arndt et al. (2013); Kalenchuk (2022); Malovichko and Rigby (2024). The improved (calibrated) stress model is expected to deliver more realistic distribution of stresses for the current mining step and should provide better prediction of the stress redistribution for the future planned mining steps.
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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 | 0.001 |
| 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".