Estimation of cyclic cryo-thermal effects on the structure and properties of coal by the thermally induced acoustic emission method
Bibliographic record
Abstract
The article considers the experimental test data on thermally induced acoustic emission (TAE) in the intact and pre-frozen-and-thawed samples of different rank lignite and bituminous coal. The authors propose and validate methodical approaches to thermal stimulation of acoustic emission effects in coal in order to assess coal susceptibility to formation of crack–porous structure under cyclic treatment by freezing and thawing. The physical preconditions and mechanisms of the acoustic emission effects are explained. The interconnections between the TAE parameters chosen for the tests and the velocity of cryogenic formation of the crack–porous structure in coal are shown. Based on the analysis of the specific features of these interconnections, the numerical acoustic emission criterion Rt is offered and substantiated for the estimation of climatic influences on the rate of structural transformations in coal. It is proved that this criterion is unexposed to interfering effect of random factors inherent to a control object such as inclusions with anomalous material constitution, size and shape of a sample, nonuniform crack network etc. It is demonstrated that the proposed criterion is highly sensitive to variation in calorific capacity of coal as a consequence of cryogenic disintegration and intensification of oxidation. It is shown that the process of cryogenic disintegration is stagewise. The scope of the discussion encompasses applicability of the obtained results. It is proved that evaluation of change in Rt in periodically sampled coal products, either under storage or haulage, allows estimation of cryogenic disintegration intensity in coal and prediction of degradation of its useful quality under specific conditions. Based on that, it is possible to obtain information for the calculation of expediency and schedule of oxidation source confinement and secondary protection of coal from climatic impacts. As compared wit the conventional methods, the key advantages of TAE approach are high measurement rate and serviceability under field conditions in the mode of express-control. It is also of no little significance that TAE method provides information about the whole volume of a tested coal sample rather about its surface as in the microexamination techniques, for example.This study has been supported by the Russian Foundation for Basic Research, Grant No. 16-05-00033 А.
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How this classification was reachedexpand
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 | 0.000 | 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) | 0.000 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".