Numerical Modeling of Complex Stress State in a Fault Damage Zone and Its Implication on Near‐Fault Seismic Activity
Bibliographic record
Abstract
Abstract Near‐fault severe seismic activity is frequently observed when excavating deep underground during various engineering projects. The present study elaborates a method to simulate the heterogeneous, complex stress state inside fractured rock mass in a fault damage zone, based on the concept of equivalent elastic compliance tensor and boundary traction method. After verifying the method with the discrete element method, the stress state of the fault damage zone composed of millions of fractures was analyzed. It is then demonstrated that the method is capable of simulating stress anomalies that could be the cause for severe seismic activity. The quantitative analysis indicates that the discrepancy between local and regional fracture densities is one of the dominant factors that produce an intensely stressed region, suggesting the use of local‐to‐regional fracture density ratio as an index to evaluate the potential for stress anomalies and its degree. Furthermore, a model parametric study on fracture properties was carried out to provide insight into the discrepancy in the likelihood of abnormal stress state between jointed host rock and fault damage zone. Lastly, b‐value was computed from thousands of possible seismic events identified in the model, by assuming seismic efficiency and scaled energy. The computed b‐value was found to fall within a reasonable range estimated from induced seismicity in deep underground mines. These results imply that the proposed method may be used to obtain a first‐order approximation of the complex rock mass stress state in fault damage zones and to evaluate the severity of seismic activity.
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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 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".