Monitoring of rock stress change using instrumented rebar rock bolts
Bibliographic record
Abstract
Abstract Rock stress is causing unwanted deformations of deep underground spaces. Large deformations increase the risk of failure. The underground excavation causes rock stress changes in the surrounding rock mass, and the resulting deformations can be measured. In this paper, we present a method to monitor stress changes in the rock mass using rebar rock bolts instrumented with strain gauges to track the stress within the bolt. Next to that, we describe in-situ testing of this method using heating-induced stress in a natural underground environment. The heating experiment aims to create stress changes using rope heaters inserted into the rock mass and located symmetrically around a single instrumented rock bolt. The heat flux induced to the rock mass leads to volume expansion. The restricted thermal expansion causes an increase in the internal rock stress conditions. These conditions create a strain that can be measured and back-calculated as the rock stress change. The instrumented rock bolt and testing setup were installed in the Underground Research Laboratory located in a granitic rock below the Aalto University campus. The single bolt experiment demonstrates how instrumented rock bolts could monitor the changes in the rock mass stress state. The system can be used as a part of a real-time rock stress monitoring system in mining and rock engineering projects. The final part of the paper describes how this monitoring system can positively affect geotechnical risk management and increase the overall safety of underground construction.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 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".