Laboratory Characterization of a Synthetic Sandstone for Tunnel Rockburst Study
Bibliographic record
Abstract
ABSTRACT: Assessment of rockburst potential in the rockmass is one of the main challenges in tunnel design. The phenomenon of rockburst is often linked with brittle failure characteristics of the rock leading to high strain-energy release and spalling, fractures, and damage around the tunnel boundary. This paper develops a synthetic sandstone as a model material for bursting rocks prepared in the laboratory to advance the study of the rockburst phenomenon. The synthetic sandstone is composed of fine-grained F-75 Ottawa sand, type I/II cement, and water. The brittle behavior of the material was studied based on the full stress-strain curve observed in the synthetic sandstone. Also, the synthetic rockburst-susceptible rock suitability is evaluated using several empirical criteria, such as strength brittleness index, burst energy coefficients, a brittleness index modified, and a strain energy storage index. The laboratory tests found that the material can be easily reproduced in different shapes and geometry with repeatable properties. The elemental testing damage characterization of the synthetic sandstone shows that the material is similar to bursting rock. The synthetic sandstone will be further expanded in laboratory-scale physical model testing using a true-triaxial cell to study the complex problem of rockburst. 1. INTRODUCTION The sudden, violent manner of rockburst is a complex phenomenon that remains a significant hazard for many deep underground excavations (Simser, 2019). Understanding the primary cause of rockburst and its interdependence enables engineers to make more informed risk management and mitigation decisions. One approach to improve the understanding of the failure process for the excavation is building a reproducible physical model under controlled circumstances in different shapes and geometry (Klammer et al., 2017). Although categorized as medium strength rocks, historical evidence has shown that rockburst can occur in this lithology (Q. M. Gong et al., 2012; Naji et al., 2019; Sun et al., 2016). Researchers have attempted to produce artificial rocks similar to natural sandstone in the past few decades. The efforts include a sintering process of natural sand grains with artificial beads, artificial cement, 3D printing, and chemical reaction utilization (David et al., 1998; Huang and Airey, 1998; Ishutov et al., 2015; Osinga et al., 2015; Rice-Birchall et al., 2021). However, these methods necessitated extensive resources and were considered limited in terms of ease of preparation.
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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 | 0.000 |
| 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) | 0.001 | 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".