MétaCan
Menu
Back to cohort

Explosive formation of coherent particle jets

2014· article· en· W2004119655 on OpenAlexaff
David L. Frost, J-F Ruel, Z. Zarei, Samuel Goroshin, Yann Grégoire, F. Zhang, A. Milne, A. W. Longbottom

Bibliographic record

VenueJournal of Physics Conference Series · 2014
Typearticle
Languageen
FieldEngineering
TopicParticle Dynamics in Fluid Flows
Canadian institutionsDefence Research and Development CanadaMcGill University
Fundersnot available
KeywordsExplosive materialConical surfaceJet (fluid)Particle (ecology)Kinetic energyMechanicsLigand cone angleMaterials sciencePhysicsClassical mechanicsComposite materialChemistryGeology

Abstract

fetched live from OpenAlex

A coherent jet of particles may be generated by accelerating a conical volume of particles by detonating a layer of explosive lining the outside of the cone. Experiments have been carried out to determine the dependence of the velocity history and coherency of the jet on the particle properties and the ratio of the masses of the particles and explosive. Steel particles form thin, coherent jets, whereas lighter glass particles lead to more diffuse jets. For steel particles, the cone angle had little effect on the coherency of the jet. The efficiency of the conversion of chemical to kinetic energy is explored by comparing the experimental jet velocity with the velocity predicted from a formulation of the Gurney method for a conical geometry. The effect of particle density and cone angle on the jet formation and development was also investigated using a multimaterial hydrocode. The simulations give insight into the extent of the deformation of the particle bed in the early stages of explosive particle dispersal.

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 score0.143
Threshold uncertainty score0.330

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 communication0.0000.001
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 head0.023
GPT teacher head0.226
Teacher spread0.203 · 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
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Physics Conference SeriesSame topicParticle Dynamics in Fluid FlowsFrench-language works237,207