An analytical solution for the nonlinear distribution of effective and total stresses in vertical backfilled stopes
Bibliographic record
Abstract
The increasing use of backfill in underground mines requires a proper evaluation of the stress state in and around the filled openings. This is, however, a relatively complex issue due, in part, to the large contrast in strength and stiffness between the backfill material and surrounding rock mass. In recent years, it has been shown that arching theory, based on limit equilibrium analysis, can be used to estimate the stress distribution in backfilled stopes. Nonetheless, many simplifications are involved in such analytical solutions and this affects the precision and significance of the calculated results. In this paper, a previously developed solution is enhanced by introducing the combined effects of non-uniform vertical stress distribution and positive pore water pressure. This leads to a more representative analytical solution, as demonstrated by successful comparisons with numerical simulations. The results indicate that the proposed solution can be used to estimate the effective and total stress state in submerged or partially submerged backfilled stopes with a simple geometry.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".