Effect of microwave treatment on the thermal properties and dynamic splitting behavior of red sandstone
Bibliographic record
Abstract
Microwave energy is a promising application in future rock breakage operations in the civil, mining, processing, and space industries. Rock engineering projects frequently experience mechanical vibration and blasting impacts. Thus, understanding the dynamic fracturing behavior of microwave-treated rock is essential for its future application in microwave-assisted mechanical rock breakage. A customized industrial microwave system with a multimode resonant cavity was used to heat red sandstone at different microwave power levels (up to 4 kW) for a constant exposure time (4 min). The rock surface temperature distribution after microwave treatment was measured by an infrared camera. Dynamic splitting tests were conducted using a split Hopkinson pressure bar (SHPB) system in combination with a high-speed camera. Experimental results indicate that the rock dynamic splitting strength is negatively related to the microwave power, and the maximum reduction is 47.8%. Microwave treatment induced an obvious nonuniform temperature distribution and C-shaped surface cracks on disc specimens. During the dynamic splitting test, the crack induced by dynamic loading always initiates from the crack tip induced by microwave irradiation and then propagates along the loading diameter. The distribution of the inner high-temperature zone in the disc specimen is symmetric along the horizontal centerline of the disc specimen.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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".