Experimental and numerical studies on dynamic crack growth in layered slate rock under wedge impact loads: part I—plane strain problem
Bibliographic record
Abstract
ABSTRACT The experimental and numerical investigations presented in this paper were carried out to determine the splitting forces and crack propagation scenarios of naturally bedded layered slate rock. Splitting loads were determined by impact splitting of regular‐sized slate blocks under plane strain test loading conditions, using a hydraulic actuator with a wedge‐shaped indenter. The mechanical properties of slate blocks required for numerical analyses were obtained from detailed experimental testing. The velocity of dynamic crack propagation in slate blocks under indenting wedge impact loading was determined using a series of strain gauge sensors. Numerical studies were carried out using ABAQUS, a general purpose, finite element analysis (FEA) program. Mode I dynamic crack propagation was simulated numerically by the gradual releasing of the restrained node on the symmetric plane of the specimens. Mode I stress intensity factors were computed for different crack lengths and the results were compared with the plane strain material fracture toughness obtained from earlier experiments/FEA. Very good agreement was obtained between analysis results and the measured fracture toughness value of slate, for the applied impact splitting load. Using the equation derived from a parametric study, of results obtained from the numerical analysis of different sizes of slate blocks, the maximum theoretical impact splitting force was determined using the plane strain fracture toughness value obtained from FEA. The difference between the loads obtained from the experimental studies and the derived empirical equation, varied between + 4.96% and −32.34%.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".