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Record W2949981663 · doi:10.1016/j.ijmst.2019.06.008

Rock support in strainburst-prone ground

2019· article· en· W2949981663 on OpenAlexafffund
Ming Cai

Bibliographic record

VenueInternational Journal of Mining Science and Technology · 2019
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsLaurentian University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsRock boltRock mass classificationExcavationGeotechnical engineeringRock burstMining engineeringUnderground mining (soft rock)RebarReinforcementEngineeringGeologyCoal miningStructural engineeringCoalWaste management

Abstract

fetched live from OpenAlex

Strainburst is the most frequently encountered type of rockburst in underground mines. Strainburst occurs when the stress near the excavation boundary reaches the peak strength of the rock mass causing it to fail suddenly and violently. To mitigate strainburst damage risk, effective rock support is needed. In strainburst-prone grounds, it is critical to have rock support components to fulfill the role of rock reinforcement first to prevent rock failure. On the other hand, well-retained and reinforced rock masses may be excessively deformed and fail violently. In such a case, yielding elements are needed in the rock support system to absorb the excess strain energy released due to rock failure. The conventional method to support strainburst-prone grounds is to install rock reinforcement system using rebar and mesh first and then install yielding support system using dynamic rockbolts at a later stage. This two-stage rock support installation process is not effective because it can adversely impact mine production schedule. This paper presents a new, patented dynamic rockbolt, which is called superbolt and is developed for rock support in burst-prone grounds. Laboratory testing confirmed that the superbolt has superb capacity to achieve the goal of reinforcing and holding rock masses. The superbolt is characterized by high dynamic energy absorption capacity, consistent performance, and the ability to withstand repeated dynamic loading. The new rockbolt can be used in a one-pass rock support system to facilitate rapid drift development in underground mines and increase mine safety and productivity.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0030.001

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 head0.010
GPT teacher head0.246
Teacher spread0.236 · 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

Citations59
Published2019
Admission routes2
Has abstractyes

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