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Record W4405171580 · doi:10.1016/j.ijmst.2024.11.003

A new scientific explanation to rock fracture-induced electromagnetic radiation process

2024· article· en· W4405171580 on OpenAlexaff
Xueqiu He, Xianghui Tian, Zhenlei Li, Menghan Wei, Majid Khan, Liming Qiu, Shengquan He, Ting Ren, Hani S. Mitri, Dazhao Song

Bibliographic record

VenueInternational Journal of Mining Science and Technology · 2024
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicEarthquake Detection and Analysis
Canadian institutionsMcGill University
Fundersnot available
KeywordsProcess (computing)Fracture (geology)GeologyMining engineeringElectromagnetic radiationGeotechnical engineeringForensic engineeringEngineeringComputer sciencePhysicsOptics

Abstract

fetched live from OpenAlex

The electromagnetic radiation (EMR) monitoring and early warning technology has experienced decades of successful applications for worldwide coal and rock dynamic disasters, yet a fundamental model unifying physical mechanism and generation process for EMR is still lacking. The effective revealing of EMR’s mechanism is crucial for dynamic disaster control and management. With this motive, a multi-scale experimental study was conducted in the earlier stage. At the micro-scale, the charge’s existence and non-uniform distribution on rock’s micro-surface were confirmed by atomic force microscope (AFM), and deduced the relationship with load changes. At the meso-scale, the time sequence synchronization and frequency domain consistency of EMR and micro-vibration (MV) in the rock fracture under load have been confirmed. Therefore, it is inferred that the vibration of the crack surface acts as the power source of rock fracture-induced EMR, and the original charge on the crack surface and the charge generated by the new crack surface are the electrical basis of EMR. Based on the above two experimental findings, this paper proposes a new mechanism of rock fracture-induced EMR defined as the electricity-vibration coupling mechanism, stating that, the vibrating charged crack generates the EMR. Subsequently, a generation model was constructed based on vibrating charged crack clusters to elucidate this mechanism. The experimental results demonstrated that the EMR waveform calculated by the model and measured by antenna exhibited good correspondence, thereby verifying the effectiveness of the constructed EMR model. The proposal of this new mechanism and the model further clarified the EMR’s mechanism induced by rock fracture. Moreover, the inter-relationship among crack propagation, vibration, and EMR was developed by this model, which could be immensely beneficial in EMR-based identification and prediction of dynamic disasters in complex mining environments worldwide.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.005
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.001

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 head0.007
GPT teacher head0.262
Teacher spread0.254 · 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 designTheoretical or conceptual
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

Citations9
Published2024
Admission routes1
Has abstractyes

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