Non-parallel double-crack propagation in rock-like materials under uniaxial compression
Bibliographic record
Abstract
Coalescence among fractures would have influence on the stability of rock masses. Deep understanding of mechanical behavior of fractured rock masses is an important mean to identify failure mechanism of geological disaster. In this study, crack propagation processing was studied through loading pre-fractured specimens of concrete block, termed as rock-like material, in uniaxial compression tests. New non-parallel double-crack geometry was introduced to observe crack coalescence. The flaw combinations are different from the normally used flaw configurations. In addition, ultrasonic detection tests were performed on the test blocks. The stress and strain data of these tests and characteristic parameters of sound wave were recorded. The stress-strain curves of each test block under the uniaxial compression test were drawn, relations among deformation characteristics and crack angle of the crack specimens, and their overall strength were analyzed. It is found that strength of the specimen decreases as crack inclination increases under two crack inclinations. The highest uniaxial compressive strength is found in the specimen with the cracks at the same angle in different directions. Based on description of the crack initiation location, crack surface and the ultimate failure patterns, failure modes of eight subtype for test blocks are divided into three categories. It is expected that the study results could be beneficial for engineering application of jointed rock masses.
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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) | 0.001 | 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".