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Record W2007415595 · doi:10.1063/1.4902635

Evolution of shock instability in granular gases with viscoelastic collisions

2014· article· en· W2007415595 on OpenAlexaff

Bibliographic record

VenueAIP conference proceedings · 2014
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsInstabilityShock (circulatory)Shock wavePiston (optics)ViscoelasticityCoefficient of restitutionInelastic collision

Abstract

fetched live from OpenAlex

Shocks in granular media have been shown to develop instabilities. We address the role that early stages of shock development have on this type of instability. We look at the evolution of shock waves driven by a piston in a dilute system of smooth inelastic disks, using both discrete-particle and continuum modelling. To mimic a realistic granular gas, viscoelastic collisions are approximated with an impact velocity threshold $u^*$ needed for inelastic collisions to occur. We show that behaviour of the shock evolution is dependent on the ratio of piston velocity to impact velocity threshold $u_p/u^*$, and the coefficient of restitution $\varepsilon$. For $u_p/u^*=2.0$, we recover shock evolution behaving similar to that observed in purely inelastic media. This is characterized by a short period where the shock front pulls towards the piston before attaining a developed structure. No pullback is seen for $u_p/u^*=1.0$. Results show the onset of instability for these stronger shocks during this evolving stage. These results suggest that the early stages of shock evolution play an important role in the shock instability.

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: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.010
GPT teacher head0.203
Teacher spread0.193 · 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

Citations3
Published2014
Admission routes1
Has abstractyes

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