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Record W2330254515 · doi:10.1061/40647(259)61

Thin Rock Support Liners Modeled with Particle Flow Code

2002· article· en· W2330254515 on OpenAlexaffabout
Dwayne D. Tannant, Caigen Wang

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeotechnical Engineering and Underground Structures
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsUltimate tensile strengthMaterials scienceShotcreteGeotechnical engineeringCompactionParticle (ecology)Composite materialEngineeringGeology

Abstract

fetched live from OpenAlex

Rapid setting, thin, spray-on polymeric liner materials are being developed for underground rock support in Canadian mines. These materials have performance characteristics that lie between those of shotcrete and mesh. Two-dimensional numerical models using Particle Flow Code (PFC) are used to model thin spray-on liners in simulated laboratory tests. The objectives were to determine how to model liners with PFC and based on these results to gain some insight about the support mechanisms provided by a liner. Direct tension tests and block punching tests were numerically simulated and used to calibrate the PFC micro-mechanical input parameters. Based on previous laboratory testing, the representative properties for a generic liner material are a tensile strength of 2MPa achieved at 50% elongation. The tensile strength is equivalent to a rupture load of 2kN per millimeter of liner per linear meter. A typical thin spray-on liner thickness used to support rock around an excavation is about 4mm. Therefore, the PFC liner models were calibrated to break at around 8kN per linear meter of liner material.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.855
Threshold uncertainty score0.729

Codex and Gemma teacher scores by category

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 head0.010
GPT teacher head0.177
Teacher spread0.167 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations13
Published2002
Admission routes2
Has abstractyes

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