A New Rock Brittleness Index Based on Crack Initiation and Crack Damage Stress Thresholds
Bibliographic record
Abstract
The brittleness of rocks is an important factor in the design of rock engineering projects, such as hydraulic fracturing, rockburst prediction, wellbore stability, and drillability. Therefore, an accurate assessment of rock brittleness is of high practical importance. However, the definition and the measurement of rock brittleness are not yet standardized. The present study proposes a new index for describing rock brittleness using crack initiation and crack damage stress thresholds for rocks with Class I stress‒strain curves. Uniaxial compressive strength (UCS) tests were conducted on fine-grained, medium-grained, and coarse-grained dolomite rock specimens in order to evaluate the performance of this index on describing brittleness. Based on the results, first, the effect of grain size on the crack initiation and crack damage stress was evaluated. Subsequently, the effect of grain size on common brittleness indexes was examined and compared to the proposed index. The results indicate that an increase in the grain size in the studied rocks increases the crack initiation, crack damage, and peak stress. It was determined that the ratio between the axial strains corresponding to the peak and crack damage stresses during the uniaxial compressive test is almost constant for all three rock types. Additionally, it was concluded, using the conventional and proposed brittleness indexes, that the brittleness index increases with an increase in grain size.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| 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".