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Record W2957476211 · doi:10.1063/1.5099142

Cavity collapse in highly heterogeneous granular mixtures with different grain size and porosity

2019· article· en· W2957476211 on OpenAlexaff
Pedro Franco Navarro, Po-Hsun Chiu, David J. Benson, Andrew Higgins, V. F. Nesterenko

Bibliographic record

VenueJournal of Applied Physics · 2019
Typearticle
Languageen
FieldMaterials Science
TopicHigh-Velocity Impact and Material Behavior
Canadian institutionsMcGill University
FundersOffice of Naval Research
KeywordsMaterials sciencePorosityMicroscale chemistryBrittlenessGrain sizeComposite materialDuctility (Earth science)Granular materialPorous medium

Abstract

fetched live from OpenAlex

The paper presents results of experimental and numerical research on the mechanism of macrocavity collapse in highly heterogeneous, porous mixtures of Al and W particles with large differences in strength, ductility, and density of components. Mixtures with different grain sizes of W particles and porosity were investigated in plane-strain, high-strain-rate conditions using the explosively driven thick-walled cylinder method. It was demonstrated that macroscopic axial symmetry was preserved, and a pattern of localized shear bands was not formed, which was typical for many previously investigated brittle and ductile materials. The grain size has an influence on the size of the inner cavity microscale instabilities that are formed by the flow of plastically deformed softer Al particles between W particles. Initial porosity did not significantly influence the macrocavity collapse in the investigated materials.

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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.534

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 head0.007
GPT teacher head0.223
Teacher spread0.216 · 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

Citations2
Published2019
Admission routes1
Has abstractyes

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