Rock strength criterion considering the effect of hydrostatic stress on lode angle effect
Bibliographic record
Abstract
Abstract Rock strength criterion is a basic subject in mining engineering and petroleum engineering. It has important guiding significances to the process of underground energy exploitation. Different rocks have different strength envelopes. Most strength criteria have only one type of envelope in π plan. Thus, these criteria cannot predict different rock strengths accurately. Most criteria consider only the hydrostatic stress and the Lode angle effects and neglect their interaction. However, based on the experimental results in this study, there is an evident interaction between the two effects. In this study, a new strength criterion is proposed considering the hydrostatic stress and Lode angle effects, as well as the effect of hydrostatic stress on the Lode angle effect. Applicable results of previous experimental data showed that the proposed strength criterion has good applicability for different rocks. Compared with other strength criteria, this criterion has the advantage of being able to adjust the strength of the Lode angle effect based on the hydrostatic stress. This advantage allows the strength criterion to show different types of strength envelopes in the π plan and to accommodate different rocks under different stress states. The effect of hydrostatic stress on the Lode angle effect of rock may be caused by the proportion of particles destroyed in the rock.
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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 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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".