MétaCan
Menu
Back to cohort

The role of numerical analysis in the study of the behaviour of hard-rock pillars

2021· article· en· W3197472608 on OpenAlexaff
Davide Elmo, G. Cammarata, Sandro Brasile

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2021
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsRock mass classificationPillarGeologyGeotechnical engineeringExcavationStability (learning theory)Stress (linguistics)Fracture (geology)Mining engineeringStructural engineeringEngineeringComputer science

Abstract

fetched live from OpenAlex

Abstract Rock pillars can be defined as the in-situ rock between two or more underground openings. However, one aspect that is seldom considered in analysis of hard rock pillars, and indirectly in synthetic rock mass models to determine rock mass strength, is the actual stress level and stress path imposed on the pillar due to the excavation sequence and the location of the pillars within the mine lay out. In this paper we propose to use numerical stress analysis to determine how stresses vary across the excavated pillars in a typical room-and-pillar mine lay out, and thus generate a spatially variable determination of pillar stability. Because of the computational difficulty associated with hybrid modelling of realistic discrete fracture networks, synthetic rock mass modelling is commonly carried out using a 2D approach. By comparing 3D and 2D results for selected cross-sections across, we believe the results of the analysis will provide the opportunity to better constrain the stability implications of a 2D approach to pillar design and synthetic rock mass modelling.

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: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.450
Threshold uncertainty score0.140

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)0.0000.000

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 head0.192
Teacher spread0.182 · 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 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

Citations3
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueIOP Conference Series Earth and Environmental ScienceSame topicRock Mechanics and ModelingFrench-language works237,207