Cave-scale Mine Modeling Challenges and a New 3D-FDEM Modeling Concept
Bibliographic record
Abstract
ABSTRACT: In cave mine modeling, it is essential to consider the evolution of rock mass from continuum to discontinuum and from interlock to disintegration. The hybrid finite-discrete element method (FDEM) presents a valuable framework for investigating the rock fracturing process, from laboratory scale, rock mass scale, to cave scale. With advancements in graphics processing unit (GPU) technology, a 3D FDEM approach can offer the potential for practical, large-scale cave mine modeling, overcoming previous computational limitations and offering new insights into caveability, fragmentation, and preconditioning processes. This paper presents a workflow for 3D cave-scale FDEM modeling, incorporating laboratory-derived parameters upscaled to field conditions using field mapping data. Finally, a conceptual 3D FDEM model with over twelve million elements was developed to simulate cave mining process that are challenging to capture using conventional continuum or discontinuum based approaches.
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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) | 0.000 | 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 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".