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Record W4321483451 · doi:10.1016/j.jrmge.2022.12.025

On the calibration and verification of Voronoi-based discontinuous deformation analysis for modeling rock fracture

2023· article· en· W4321483451 on OpenAlexaff
Kaiyu Zhang, Feng Liu, Kaiwen Xia, Ying Xu, Peng Dong, Changyi Yu

Bibliographic record

VenueJournal of Rock Mechanics and Geotechnical Engineering · 2023
Typearticle
Languageen
FieldEngineering
TopicRock Mechanics and Modeling
Canadian institutionsUniversity of Toronto
FundersNational Natural Science Foundation of China
KeywordsVoronoi diagramCalibrationSensitivity (control systems)Deformation (meteorology)Overburden pressureFracture (geology)GeologyDiscontinuous Deformation AnalysisCompression (physics)Rock mechanicsGeotechnical engineeringShear (geology)MechanicsStructural engineeringGeometryMaterials scienceMathematicsFinite element methodEngineeringPhysicsComposite materialStatistics

Abstract

fetched live from OpenAlex

Since its introduction, discontinuous deformation analysis (DDA) has been widely used in different areas of rock mechanics. By dividing large blocks into subblocks and introducing artificial joints, DDA can be applied to rock fracture simulation. However, parameter calibration, a fundamental issue in discontinuum methods, has not received enough attention in DDA. In this study, the parameter calibration of DDA for intact rock is carefully studied. To this end, a subblock DDA with Voronoi tessellation is presented first. Then, a modified contact constitutive law is introduced, in which the tensile and shear meso-strengths are modified to be independent of the bond lengths. This improvement can prevent the unjustified preferential failure of short edges. A method for imposing confining pressure is also introduced. Thereafter, sensitivity analysis is performed to investigate the influence of the calculated parameters and meso-parameters on the mechanical properties of modeled rock. Based on the sensitivity analysis, a unified calibration procedure is suggested for both cases with and without confining pressure. Finally, the calibration procedure is applied to two examples, including a biaxial compression test. The results show that the proposed Voronoi-based DDA can simulate rock fracture with and without confining pressure very well after careful parameter calibration.

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 score0.862
Threshold uncertainty score0.387

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 head0.012
GPT teacher head0.207
Teacher spread0.195 · 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

Citations27
Published2023
Admission routes1
Has abstractyes

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