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Record W2758024603 · doi:10.20431/2454-9460.0301003

Roadway Support Technology with Sliding Cracking Surrounding Rock under Tectonic Stress

2017· article· en· W2758024603 on OpenAlexaff
Dongyin Li, Ning Li, Weisheng Du

Bibliographic record

VenueInternational Journal of Mining Science · 2017
Typearticle
Languageen
FieldEngineering
TopicGeotechnical and Geomechanical Engineering
Canadian institutionsUniversity of British Columbia
FundersNational Natural Science Foundation of China
KeywordsCrackingTectonicsGeologyStress (linguistics)Geotechnical engineeringMining engineeringForensic engineeringMaterials scienceSeismologyEngineeringComposite material

Abstract

fetched live from OpenAlex

The west ventilation roadway in Damoling Coal Mine in China suffered the serious impact of tectonic stress.The deformation of the roadway was observed and the asymmetric deformation behavior was analyzed.FLAC3D was used to simulate the distribution of the stress, displacement and plastic zone with the original support.The drawbacks of the original support scheme were deficient support resistance, no effect on the asymmetric deformation and no support effect on the floor.The improved support scheme named "symmetric integrated support technology using long anchors and anchor cables" was proposed.The new support suggested increasing the length of anchors, optimizing the interval of anchors, and installing anchors in the floor.The simulation results of FLAC3D verify the improved support scheme.The deformation data of the roadway after conducting the improved support scheme was obtained.The deformation value showed a remarkable decrease and the asymmetric deformation characteristic was improved obviously.The successful application of the supporting technology provides a reference for roadways with similar geological conditions.

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 score0.003
Threshold uncertainty score0.006

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 communication0.0000.001
Open science0.0010.000
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 head0.013
GPT teacher head0.261
Teacher spread0.249 · 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

Citations0
Published2017
Admission routes1
Has abstractyes

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