Effect of heterogeneity of brittle rock on micromechanical extensile behavior during compression loading
Bibliographic record
Abstract
A grain‐based Universal Distinct Element Code model was developed to generate a deformable polygonal grain‐like structure to simulate the microstructure of brittle rock. It takes into account grain‐scale heterogeneity including microgeometric heterogeneity, grain‐scale elastic heterogeneity, and microcontact heterogeneity. The microgeometric heterogeneity can be used to match the grain size distribution of the rock. The discrete element approach is able to simulate the microheterogeneity caused by elastic variation and contact stiffness anisotropy. The modeling approach was evaluated using Lac du Bonnet granite and Äspö Diorite. The microheterogeneity played an important role in controlling both the micromechanical behavior and the macroscopic response when subjected to uniaxial compression loading. The crack‐initiation stress was found to be controlled primarily by the microscale geometric heterogeneity, while the microcontact heterogeneity controlled the strength characteristics. The effect of heterogeneity on the distribution and evolution of tensile stresses and associated extension cracks was also examined.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".