An Experimental Study on Mechanical Behavior of Parallel Joint Specimens under Compression Shear
Bibliographic record
Abstract
In order to investigate the influence of the joint on the failure mode, peak shear strength, and shear stress‐strain curve of rock mass, the compression shear test loading on the parallel jointed specimens was carried out, and the acoustic emission system was used to monitor the loading process. The joint spacing and joint overlap were varied to alter the relative positions of parallel joints in geometry. Under compression‐shear loading, the failure mode of the joint specimen can be classified into four types: coplanar shear failure, shear failure along the joint plane, shear failure along the shear stress plane, and similar integrity shear failure. The joint dip angle has a decisive effect on the failure mode of the specimen. The joint overlap affects the crack development of the specimen but does not change the failure mode of the specimen. The joint spacing can change the failure mode of the specimen. The shear strength of the specimen firstly increases and then decreases with the increase of the dip angle and reaches the maximum at 45°. The shear strength decreases with the increase of the joint overlap and increases with the increase of the joint spacing. The shear stress‐displacement curves of different joint inclination samples have differences which mainly reflect in the postrupture stage. From monitoring results of the AE system, the variation regular of the AE count corresponds to the failure mode, and the peak value of the AE count decreases with the increase of joint overlap and increases with the increase of joint spacing.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".