Effect of surface retaining elements on rock stability: laboratory investigation with sand powder 3D printing
Bibliographic record
Abstract
Abstract This study aims to investigate the beneficial effects of surface retaining elements (SREs) on the mechanical behaviors of bolted rock and roadway stability. 3D printing (3DP) technology is utilized to create rock analogue prismatic specimens for conducting this investigation. Uniaxial compression tests with acoustic emission (AE) and digital image correlation techniques have been conducted on 3DP specimens bolted with different SREs. The results demonstrate that the strength and modulus of elasticity of the bolted specimens show a positive correlation with the area of the SRE; the AE characteristics of the bolted specimens are higher than those of the unbolted specimen, but they decrease with an increase in SRE area, thus further improving the integrity of the bolted specimens. The reinforcement effect of SREs on the surrounding rock of roadways is further analyzed using numerical modelling and field test. The results provide a better understanding of the role of SREs in rock bolting and the optimization of rock bolting design. Furthermore, they verify the feasibility of 3DP for rock analogues in rock mechanics tests.
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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) | 0.000 | 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".