Minimum-Time Path (Brachistochrone) Analysis for Extreme Flow Slide Mobility in High-End Waste Dumps: Integrating Pore Pressure and Dynamic Rheology
Bibliographic record
Abstract
Abstract High mobility in flow slides from high-end waste dumps often arises from complex interactions among pore pressure, basal friction, and path geometry. This study introduces a minimum-time path (Brachistochrone) reference, adapted from classical frictionless descent theory, to quantify how real flow slides deviate from an idealized baseline. Analysis of 46 documented events incorporates Bishop’s pore pressure coefficient and a velocity-dependent (Voellmy) rheology, revealing threshold conditions for extreme mobility. The results show that pore pressure ratios exceeding 0.4 and basal friction angles below 10° correlate strongly with increased mobility, particularly where narrow path apertures intensify velocity and turbulence. By contrasting observed runout distances with the Brachistochrone-based frictionless reference, these findings highlight the significance of liquefaction-prone conditions and provide field-oriented guidelines for dynamic friction angle selection, turbulence calibration, and pore pressure estimation. This approach offers a clearer theoretical basis for predicting flow slide mobility in active mining environments, supporting more effective risk management and design practices. Highlights Refines the classification system for flow slide mobility using a database of 46 coal mine waste dump failures in the Canadian Rockies. Explores the interplay of path geometry, pore pressure, and basal shear resistance in influencing flow slide mobility, offering practical guidelines and fitting equations. Highlights the significant role of turbulence and path aperture in the dynamic behavior of flow slides.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".