Multistage triaxial testing of intact rock: volumetric strain-based methods applied to rock slope design
Bibliographic record
Abstract
Triaxial testing of intact rock is commonly undertaken to provide input parameters for rock slope design. Multistage triaxial tests offer economies in terms of time, sample quantities and costs, and for these reasons have found commonplace in engineering practice. Volumetric strain-based methods are sometimes employed for multistage testing to minimise damage accumulation in early test stages. This is done by (1) terminating early test stages at volumetric strain reversal, (2) straining the final stage until failure occurs, then (3) inferring a peak stress for the earlier stages based on a correction factor derived from the final stage. This paper provides a review of multistage triaxial testing along with fundamental rock mechanics theories that underpin the volumetric strain-based multistage testing method. Results from single and multistage tests are then used to demonstrate possible errors that may result if multistage tests are conducted over a range of stresses where compressive failure of intact rock is controlled by different failure mechanisms. Finally, some examples and discussion are provided to demonstrate the possible impact that these errors may have on rock slope stability assessments.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".