The effect of loading contact angle on the tensile behavior of rock disks
Bibliographic record
Abstract
Tensile strength is one of the most important characteristics of rock masses that could govern the stability of rock structures. Due to difficulties in its direct measurements, indirect methods such as the Brazilian test have been developed to assess the tensile strength of laboratory-scale rock material. This study considers the effect of loading contact angle on the indirect tensile strength of rock-like disks by adopting experimental and discrete element methods. Several experimental specimens made of synthetic materials were examined under diametrical loading, and consequently, a numerical model using PFC3D was calibrated accordingly. Then, the impacts of the loading contact angle (θ) on the tensile strength, failure pattern, and contact force chain were investigated in detail. The results indicated that as θ increases from 0°, suggested by ASTM, to 90°, the tensile state is dominated at the specimen center, whereas for angles greater than 90°, the dominant stress state changed to compression. Also, while σxx (tensile stress) at the center of the disk did not change for θ below 40°, the σyy (compressive stress) and σzz (out-of-plan normal stress) increased after θ =30°. The analysis of developed cracks suggested that when θ is lower than 30°, the percentage of tensile and shear cracks were constant (80% and 20%, respectively). As the loading contact angle increased, tensile cracks decreased, whereas the other increased. By analyzing the failed specimens, three categories of crack patterns and two categories of contact force chains were identified.
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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".