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Record W1962238799 · doi:10.1002/nag.2368

On modeling of discrete propagation of localized damage in cohesive‐frictional materials

2015· article· en· W1962238799 on OpenAlexaff
Ehsan Haghighat, S. Pietruszczak

Bibliographic record

VenueInternational Journal for Numerical and Analytical Methods in Geomechanics · 2015
Typearticle
Languageen
FieldEngineering
TopicNumerical methods in engineering
Canadian institutionsMcMaster University
Fundersnot available
KeywordsDiscontinuity (linguistics)BrittlenessConstitutive equationUltimate tensile strengthShear (geology)Cohesive zone modelFracture mechanicsRepresentation (politics)Structural engineeringMaterials scienceGeotechnical engineeringMechanicsGeologyFinite element methodEngineeringPhysicsMathematicsMathematical analysisComposite materialLaw

Abstract

fetched live from OpenAlex

Summary In this paper, the problem of propagation of localized deformation associated with formation of macrocracks/shear bands is studied in both tensile and compressive regimes. The main focus here is on enhancement of the constitutive law with embedded discontinuity to provide a discrete representation of the localization phenomenon. This has been accomplished by revising the formulation and coupling it with the level‐set method for tracing the propagation path. Extensive numerical studies are conducted involving various fracture modes, ranging from brittle to frictional, and the results are compared with the experimental data as well as those obtained using XFEM methodology. Copyright © 2015 John Wiley & Sons, Ltd.

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)0.001
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 score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.048
GPT teacher head0.382
Teacher spread0.334 · 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

Citations44
Published2015
Admission routes1
Has abstractyes

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