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Record W4382599443 · doi:10.1201/9781003348030-298

The use of an innovative fiber optic methodology to capture the axial response of rib spacing and grout annulus effects on grouted rock bolts

2023· book-chapter· en· W4382599443 on OpenAlexaff
Kieran Moore, Nicholas Vlachopoulos

Bibliographic record

Venuenot available
Typebook-chapter
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsRoyal Military College of Canada
Fundersnot available
KeywordsGroutAnnulus (botany)Geotechnical engineeringStructural engineeringGeologyMaterials scienceEngineeringComposite material

Abstract

fetched live from OpenAlex

The fully grouted rock bolt is used extensively as a ground support element within various underground projects. The physical testing of available research is largely focused on small embedment length samples as historic monitoring techniques and technologies have noted limitations as it pertains to capturing the mechanical behaviour of longer samples. To address this gap, the authors have developed a monitoring technique using fiber optics. This methodology captures the axial response by producing a continuous strain profile along the length of the rebar as well as the representative confining medium across a wide range of loading. This paper summarizes the results of a robust laboratory investigation to determine the impact of rib spacing arrangements as well as the size of grout annulus on bolt performance as it relates to rock bolt behaviour. The efforts of such results will be used to improve rock bolt support lengths for ground design purposes.

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: Methods · Consensus signal: none
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
Bibliometrics0.0000.001
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 head0.038
GPT teacher head0.250
Teacher spread0.212 · 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
GenreMethods

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

Citations1
Published2023
Admission routes1
Has abstractyes

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