Analytical solution for estimating the minimum required strength of sill mat by considering failure due to rock wall closure
Bibliographic record
Abstract
Underhand cut-and-fill mining has been widely used in underground mining operations, especially when the rock mass or orebody is of poor quality or prone to rockburst due to high stress. In such cases, mining workers should carry out all production activities under the cemented backfill roof or sill mat instead of a highly fractured and unstable rock roof or a strong rock roof with a high potential of rockburst. Therefore, the stability and required strength of the sill mat are critical issues for mining engineers. In 1991, Mitchell considered that sill mat could fail by caving, sliding, rotation, and flexure. Mitchell also proposed an analytical solution to determine the minimum required strength of the sill mat for each type of failure based on two stiff or immobile rock walls. However, recent publications using numerical modeling and field measurements indicate that the compressive stresses in the sill mat induced by rock wall closure due to a stope excavation beneath the sill mat can be significant. It is thus highly necessary to investigate the required strength of the sill mat by considering rock wall closure. In this study, the crushing failure of sill mat due to rock wall closure generated by underground excavation and a new failure mode called "crushing and caving" is revealed by numerical modeling. An analytical solution corresponding to each failure mode is then developed to estimate the minimum required cohesion () of the sill mat. A criterion is also proposed to determine if the sill mat fails by crushing or crushing-and-caving failure. The proposed analytical solution does not involve any correction coefficients. The validity of the proposed analytical solution is demonstrated by numerical modeling. The proposed analytical solution can thus be employed to predict the of sill mat subjected to wall closure generated by underlying stope excavation.
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.
How this classification was reachedexpand
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 | 0.001 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".