Crack Damage Evaluation of Crystalline Rocks by Means of Acoustic Emission Technique
Bibliographic record
Abstract
The crack damage progression in crystalline rocks is approximated in laboratory by means of rigorous strain measurement and/or monitoring of Acoustic Emission (AE) activity. When both means are used, they are treated independently for quantification of damage in the rock. This paper is investigating a new method to combine the AE and strain data in a unified function to calculate the balance of stored and released energy in the rock due to loading (strain energy) and micro-cracking respectively. This method introduces a new solution for measurement and quantification of crack damage in rock and also provides a tool to investigate the brittleness of different rock types. Unconfined Compressive Strength (UCS) testing of six different rock types with strain measurement and AE monitoring was performed for this study. The application of the new method to the data collected from the UCS tests indicates the difference between the behaviour of the various rock types in terms of sudden energy release at the onset of CI threshold and the difference in the storability of strain energy before and after CI and CD thresholds.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".