Investigating the effects of geothermally active temperature conditions on fully grouted rock bolts with distributed fiber optic sensors
Bibliographic record
Abstract
A series of laboratory pull-out tests was conducted to study the effects of temperature on the performance and behaviours of fully grouted rock bolt specimens cured within a specific temperature range, as well as for different durations. Each specimen consisted of a 20M rebar bolt at 1300 mm embedment length grouted inside a Schedule 80 steel pipe using Portland cement grout at a 0.4 water-to-cement ratio. Two temperatures (20 °C and 45 °C) were explored to investigate the effects of geothermally active temperature conditions on fully grouted rock bolts. Distributed fiber optic sensors were employed to provide continuous strain profiles along the entire embedment length to observe micro-mechanisms and monitor internal specimen temperature change during testing. The specimens cured at 45 °C generally resulted in higher grout UCS (in certain cases 25%-50% higher) compared to those at 20 °C; the ultimate capacity was not significantly impacted as the specimens’ embedment length allowed full development of the rock bolt’s capacity. The resulting strain profile trends showed generally higher strains experienced by the shorter (i.e. 3-d) curing duration specimens under both curing temperatures compared to long-term curing. The 45 °C specimens generally experienced lower strains and faster strain profile attenuation compared to specimens cured at 20 °C. Understanding these effects and further analysis of FGRB specimen behaviours over time provide insights for mobilized and critical embedment lengths, capacity development, and support system stabilization. This paper highlights the results of this study and aims to bridge selected gaps in existing literature with a view to aid practitioners.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".