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Record W4402275633 · doi:10.1139/cgj-2024-0071

Effect of microwave heating on rock damage and energy evolution

2024· article· en· W4402275633 on OpenAlexvenueno aff
Li Tan, Wei Wang, Guangbo Chen, Qinghai Li

Bibliographic record

VenueCanadian Geotechnical Journal · 2024
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsnot available
FundersNatural Science Foundation of Inner MongoliaNational Natural Science Foundation of China
KeywordsGeotechnical engineeringGeologyForensic engineeringEnvironmental scienceMining engineeringEngineering

Abstract

fetched live from OpenAlex

Rock fragmentation efficiency can be increased by microwave heating. The mechanical properties and energy evolution characteristics of coarse sandstone specimens under different microwave heating conditions are compared in this paper. The effects of microwave heating time and power on coarse sandstone specimens of peak stress, elastic modulus, brittleness index, damage variable, and impact energy index are analyzed. The results indicate that the microwave heating power and microwave heating time are inversely proportional to peak stress and elastic modulus and directly proportional to peak strain. With the increase of microwave heating power and microwave heating time, the brittleness index and damage variable of rock specimens increase, the impact energy index decreases. The microwave heating power and microwave heating time increase the rock brittleness index. The energy absorption rate of rock specimens decreases with the increase of microwave heating time. The impact energy index is inversely proportional to microwave heating power and microwave heating time. High-power and long-time microwave heating can reduce the possibility of rockbursts and the intensity of potential dynamic disasters. The research conclusion can provide the theoretical and technical basis for breaking rock by microwave heating.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.005
GPT teacher head0.195
Teacher spread0.191 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2024
Admission routes1
Has abstractyes

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