Dynamic rock tests using split Hopkinson (Kolsky) bar system – A review
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Bibliographic record
Abstract
Dynamic properties of rocks are important in a variety of rock mechanics and rock engineering problems. Due to the transient nature of the loading, dynamic tests of rock materials are very different from and much more challenging than their static counterparts. Dynamic tests are usually conducted using the split Hopkinson bar or Kolsky bar systems, which include both split Hopkinson pressure bar (SHPB) and split Hopkinson tension bar (SHTB) systems. Significant progress has been made on the quantification of various rock dynamic properties, owing to the advances in the experimental techniques of SHPB system. This review aims to fully describe and critically assess the detailed procedures and principles of techniques for dynamic rock tests using split Hopkinson bars. The history and principles of SHPB are outlined, followed by the key loading techniques that are useful for dynamic rock tests with SHPB (i.e. pulse shaping, momentum-trap and multi-axial loading techniques). Various measurement techniques for rock tests in SHPB (i.e. X-ray micro computed tomography (CT), laser gap gauge (LGG), digital image correlation (DIC), Moiré method, caustics method, photoelastic coating method, dynamic infrared thermography) are then discussed. As the main objective of the review, various dynamic measurement techniques for rocks using SHPB are described, including dynamic rock strength measurements (i.e. dynamic compression, tension, bending and shear tests), dynamic fracture measurements (i.e. dynamic imitation and propagation fracture toughness, dynamic fracture energy and fracture velocity), and dynamic techniques for studying the influences of temperature and pore water.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it