Application of Discrete Fracture Networks (DFN) In the Stability Analysis of Delabole Slate Quarry, Cornwall, UK
Bibliographic record
Abstract
The failure mechanism of rock slopes is mainly controlled by the strength and orientation of discontinuities within the rock mass. A realistic representation of the joint network within the rock mass is therefore an essential component of stability analysis of rock structures (e.g. rock slopes, tunnels etc.). Discontinuity persistence and connectivity are significant parameters which control the stability of rock slopes. A small percentage of rock bridges on the discontinuity surface can significantly increase its strength and prevent slope failure. Discontinuities within the rock mass are rarely fully connected. In practice, however, discontinuities are often assumed fully persistent due to the difficulties both in mapping and simulation of non-persistence. Discrete fracture networks (DFN) provide a rigorous and convenient tool for the simulation of joint systems within a rock mass. Utilizing statistical methods, DFNs consider the stochastic nature of some key parameters (e.g. persistence and orientation) within numerical models. Discrete fracture network engineering is increasingly used due to recent developments in discontinuity data acquisition techniques (e.g. ground-based digital photogrammetry and laser scanning). Recent development in geomechanical modelling codes and increased computing power have also allowed to either import DFN’s into models or to generate DFN’s within the numerical modelling code itself (e.g. 3DEC). This paper describes the use of photogrammetry at the Delabole slate quarry in Cornwall, UK for remotely acquiring key discontinuity parameter data (orientation, intensity and length) and its subsequent use in developing statistically validated discrete fracture network parameters. The 3D distinct element code, 3DEC, is used for the DFN generation and subsequent stability analysis. Several realizations of the 3DEC-DFN models are run to investigate the stochastic nature of discontinuities within the quarry and their potential influence on the stability of the pit. Finally the simulation results are used to determine the slope instability mechanisms and determine the most likely areas of potential instability.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".