Development of thin, spray-on liner and composite superliner area supports for damage mitigation in blast- and rockburst-induced rock failure events
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Research has been performed for the Workplace Safety and Insurance Board of Ontario (WSIB) to characterize the capabilities of innovative mining support agents, designated as spray-on lining materials (TSL's), as well as combinations of TSL's and conventional spray supports, for mitigating dynamic failure effects created by simulated rockbursts. The assessment of support capabilities of TSLs and ultra-thin hybrid liner supports (superliners) is novel and constitutes work that is unique in the field of underground excavation support design. This study has been performed to assess the capabilities of TSL and conventional spray-on support systems for preventing rock and support material damage that often results due to rockbursting. In this research, TSL products and superliner combinations of each with ultra-thin shotcrete or fibrecrete layers (at 5 and 3 cm thicknesses, respectively) have been tested. Support performance was studied using field scale explosive detonation trials to simulate dynamic failure effects that are known to develop during typical rockburst events. Multiple seismic and high speed photographic monitoring techniques were used to provide detailed information concerning rock motion, surface fracturing, ejected fragment motion and support liner survivability characteristics. The results of this study have validated that thin, spray-on linings (TSL's) and variant layer combinations may be as effective as or better than conventional support materials for mitigating rockburst or like damage in highly stressed mine environments.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.000 | 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 it