Stochastic Slope Stability Analysis Accounting for Heterogeneity in Rock Mass
Bibliographic record
Abstract
Rock mass heterogeneity could influence the stability of open pit slope. As such, slope stability approach that accounts for rock mass heterogeneity could provide an efficient slope design. This thesis proposes and implements stochastic modelling approach that characterizes the spatial variability of geomechanical properties to evaluate the stability of pit slopes in an iron ore open pit mine. 3D spatial models of geomechanical properties are developed to quantify the heterogeneity of the rock mass and to identify potential risk of pit wall failure by accounting for the influence of joints orientations with respect to the pit wall. The block models of the geotechnical attributes were then embedded as input into a discretized 3D limit equilibrium model to conduct stochastic heterogeneity stability analysis of the pit slopes. The modeling results is used to determine the probability of pit wall failure at different pit sectors which enables optimization of pit slope design.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 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".