Understanding the anisotropic stress–strain behavior of heterogeneous slate in uniaxial compressive strength testing
Bibliographic record
Abstract
Strain measurements during uniaxial compressive strength (UCS) testing and their subsequent interpretation to obtain elastic parameters are relatively straightforward for most rocks. However, for slates, which are foliated metamorphic rocks characterized by significant anisotropy, the dependence of elastic properties on the orientation of foliation complicates the measurement and interpretation of strain data. In this study, a series of wave propagation velocity tests and UCS tests are conducted on cylindrical and prismatic slate specimens to gain a better understanding of how to obtain and process deformability and strength results. Wave propagation velocity results demonstrate an increase with the dip of foliation planes crossed, which is consistent with previous studies. Based on UCS test results, two methodologies are considered for obtaining transversely isotropic deformability parameters: the least-squares method and the recently proposed generalized reduction gradient (GRG) algorithm. Their performance is assessed in the context of potentially variable and limited amounts of data. GRG algorithms provide an enhanced analysis technique for estimating anisotropic elastic properties when dealing with limited or heterogeneous laboratory test data. Different strength models have also been considered, including the classic Jaeger’s weakness plane (JPW) and its subsequent modification, i.e. 2HBJPW. The 2HBJPW approach has proven to be more consistent with the obtained results and enhances the representation of the strength properties of slates. Additionally, a finite element method (FEM) numerical approach is employed to compare results with analytical and experimental ones, demonstrating a good match, thereby offering calibrated inputs for rock engineering applications.
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How this classification was reachedexpand
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 | 0.000 | 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 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".