Deformation and failure characteristics and fracture evolution of cryptocrystalline basalt
Bibliographic record
Abstract
Cryptocrystalline basalt is one of the two major types of rocks exposed in the super large-scale underground powerhouse in Baihetan hydropower station in China. The rock of this type shows various site-specific mechanical responses (e.g. fragmentation, fracturing, and relaxation) during excavation. Using conventional triaxial testing facility MTS 815.03, we obtained the stress–strain curves, macroscopic failure characteristics, and strength characteristics of cryptocrystalline basalt. On this basis, evolution of crack initiation and propagation was explored using the finite-discrete element method (FDEM) to understand the failure mechanism of cryptocrystalline basalt. The test results showed that: (1) under different confining stresses, almost all the pre-peak stress–strain curves of cryptocrystalline basalt were linear and the post-peak stresses decreased rapidly; (2) the cryptocrystalline basalt showed a failure mode in a form of fragmentation under low and medium confining stresses while fragmentation-shear coupling failure dominated at high confining stresses; and (3) the initial strength ratio (σci/σf, where σci and σf are the crack initiation strength and peak strength, respectively) ranged from 0.45 to 0.55 and the damage strength ratio (σcd/σf, where σcd is the crack damage strength) exceeded 0.9. The stress–strain curve characteristics and failure modes of cryptocrystalline basalt could be reflected numerically. For this, FDEM simulation was employed to reveal the characteristics of cryptocrystalline basalt, including high σcd/σf values and rapid failure after σcd, with respect to the microscopic characteristics of mineral structures. The results showed that the fragmentation characteristics of cryptocrystalline basalt were closely related to the development of tensile cracks in rock samples prior to failure. Moreover, the decrease in degree of fragmentation with increasing confining stress was also correlated with the dominant effect of confining stress on the tensile cracks.
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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 | 0.000 | 0.000 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".