Stick, slip, and opening of wavy frictional faults: A numerical approach in two dimensions
Bibliographic record
Abstract
We use a two‐dimensional displacement discontinuity method (DDM) for quasi‐static boundary value problems to investigate sinusoidal faults of finite length in an otherwise homogeneous and isotropic elastic material. The DDM incorporates a complementarity algorithm to enforce appropriate contact boundary conditions along the model fault. The numerical solution for the model sinusoidal fault converges to the analytical solution for a straight fault of finite length as the ratio amplitude/wavelength goes to zero. It does not converge to the analytical solution for an infinite sinusoidal interface as the ratio distance/wavelength goes to zero. We provide stick, slip, and opening distributions along wavy faults with a range of uniform coefficients of friction, amplitude/wavelength ratios, and wave numbers. As the number of sinusoidal waves or the amplitude/wavelength is increased, mean slip decreases. Additionally, the fault geometry causes slip to deviate significantly from the elliptical distribution of a planar fault. We demonstrate that the displacement discontinuity of wavy faults cannot be prescribed a priori. This necessitates implementation of the complementarity algorithm and precludes an analytical solution. We employ the terms lee and stoss instead of releasing and restraining bends because a local minimum in slip may occur along lee sides, as well as stoss sides. In some cases, lee sides stick while stoss sides slip. Trends in the slip perturbation can be explained by the angular relationship between the local fault trace and the orientation of the remote principal stresses; however, the displacement discontinuity along a wavy model fault cannot be explained by this relationship alone.
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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 | 0.002 |
| 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 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".