Premonitory acoustic emissions and stick‐slip in natural and smooth‐faulted Westerly granite
Bibliographic record
Abstract
A stick‐slip event was induced in a cylindrical sample of Westerly granite containing a preexisting natural fault by loading at constant confining pressure of 150 MPa. Continuously recorded acoustic emission (AE) data and computer tomography (CT)‐generated images of the fault plane were combined to provide a detailed examination of microscale processes operating on the fault. The dynamic stick‐slip event, considered to be a laboratory analog of an earthquake, generated an ultrasonic signal that was recorded as a large‐amplitude AE event. First arrivals of this event were inverted to determine the nucleation site of slip, which is associated with a geometric asperity on the fault surface. CT images and AE locations suggest that a variety of asperities existed in the sample because of the intersection of branch or splay faults with the main fault. This experiment is compared with a stick‐slip experiment on a sample prepared with a smooth, artificial saw‐cut fault surface. Nearly a thousand times more AE were observed for the natural fault, which has a higher friction coefficient (0.78 compared to 0.53) and larger shear stress drop (140 compared to 68 MPa). However at the measured resolution, the ultrasonic signal emitted during slip initiation does not vary significantly between the two experiments, suggesting a similar dynamic rupture process. We propose that the natural faulted sample under triaxial compression provides a good laboratory analogue for a field‐scale fault system in terms of the presence of asperities, fault surface heterogeneity, and interaction of branching faults.
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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 | 0.000 |
| 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 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".