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Record W4388429862 · doi:10.2991/978-94-6463-258-3_65

Application of Continuum-Based Voronoi Tessellated Models for Simulating Brittle Damage and Failure in Hard Rocks

2023· book-chapter· en· W4388429862 on OpenAlexfundno aff
Navid Bahrani, Yalin Li, Farzaneh Hamediazad, Soheil Sanipour, Fatemeh Salehi Amiri

Bibliographic record

VenueAtlantis highlights in engineering/Atlantis Highlights in Engineering · 2023
Typebook-chapter
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsnot available
FundersNatural Sciences and Engineering Research Council of CanadaMitacsDalhousie University
KeywordsVoronoi diagramBrittlenessGeologyMaterials scienceGeometryMathematicsComposite material

Abstract

fetched live from OpenAlex

Voronoi tessellations are commonly used in discontinuum numerical models to simulate the microstructure of brittle rocks.In this approach, the model domain is divided into several randomly generated polygonal blocks.Discontinuum-based Voronoi Tessellated Models (VTM) capture the brittle rock failure process more realistically than conventional continuum models.However, their higher computational costs often limit their practicality.This paper presents the applications of a continuum-based VTM for simulating brittle rock damage and failure at core and rock mass scales.The examples reviewed include: 1) laboratory behavior of a marble; 2) drilling-induced core damage; 3) failure mechanism of hard rock pillars; and 4) v-shaped notch formation around a circular tunnel.It is concluded that a properly calibrated continuum-based VTM can be used as a reliable tool for analyzing a wide range of geomechanical problems.

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)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.049
Threshold uncertainty score0.098

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0020.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.198
Teacher spread0.188 · 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 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

Citations2
Published2023
Admission routes1
Has abstractno

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Same venueAtlantis highlights in engineering/Atlantis Highlights in EngineeringSame topicRock Mechanics and ModelingFrench-language works237,207