Application of a Novel Local Dynamic Weakening Model Coupled with Smooth-joint Contact in the Simulation of Fault Ruptures and Laboratory Earthquakes
Bibliographic record
Abstract
Abstract Discrete-element-method (DEM) codes were developed in the field of rock mechanics. Compared to continuum codes, it has many advantages such as allowing larger grain displacements, detachment of grains, and simulation of discrete fractures. However, the disadvantage of DEM codes in the simulation of higher confining pressure triaxial tests were not previously discussed. In this study, we explored how the non-Dirac-delta distribution of contact forces controls the fault rupture initiation, and its impact on fault rupture propagation under high confining pressure. Based on the above study, a novel local dynamic weakening model was proposed and incorporated into the smooth-joint (SJ) contact model. The dynamic weakening model is tested with simulations of experiments conducted under high confining pressures. It is shown to be successful at reproducing realistic fault rupture behaviors, and the synthetic acoustic emission (AE) characteristics including magnitude-frequency relationships and fractal dimensions match those in the experiment.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".