Performance evaluation of granite rock based on the quantitative piezoceramic sensing technique
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Granite is a common engineering material that exhibits complex mechanical properties under external loads. This study conducted experimental research and analysis in conjunction with the active monitoring technology of piezoelectric ceramics. A quantitative analysis method for the mechanical properties of rock materials based on piezoelectric health monitoring was established, and for the first time, the piezoelectric monitoring results of rock were mapped and compared with the uniaxial compression performance indicators of rock. In this study, two sets of cyclic impact experiments were conducted on granite samples using a drop hammer. The piezoelectric signals of the granite samples were detected using piezoelectric ceramic active sensing technology. A piezoelectric ceramic damage monitoring method was proposed, and the damage factor of the granite samples was calculated using the wavelet packet energy method. Subsequently, uniaxial compression experiments were performed on the damaged granite samples to obtain mechanical performance data. Finally, a mathematical relationship model was established between the piezoelectric signal and the uniaxial compressive strength of the rocks. It was found that the damage factor of the piezoelectric monitoring signal of the damaged rock were linearly related to the uniaxial compressive strength of the damaged rock.
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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 | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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 it