MétaCan
Menu
Back to cohort
Record W2572863590 · doi:10.1063/1.4971701

Fracture of explosively compacted aluminum particles in a cylinder

2017· article· en· W2572863590 on OpenAlexaff
David L. Frost, Jason Loiseau, Samuel Goroshin, Fan Zhang, Alec Milne, A. W. Longbottom

Bibliographic record

VenueAIP conference proceedings · 2017
Typearticle
Languageen
FieldEngineering
TopicEnergetic Materials and Combustion
Canadian institutionsDefence Research and Development CanadaMcGill University
Fundersnot available
KeywordsExplosive materialMaterials scienceCompactionAluminiumComposite materialMetal foamFracture (geology)CylinderShock waveMetallurgyMechanicsChemistry

Abstract

fetched live from OpenAlex

The explosive compaction, fracture and dispersal of aluminum particles contained within a cylinder were investigated experimentally and computationally. The aluminum particles surrounded a central, cylindrical high explosive burster charge and were weakly confined in a cardboard tube. The compaction and fracture of the particles were visualized with flash radiography and the subsequent fragment dispersal was recorded with high-speed photography. The aluminum fragments produced were much larger than the original aluminum particles and similar in shape to those generated from the explosive fracture of a solid ductile metal cylinder, suggesting that the shock transmitted into the aluminum compacted the powder to near solid density. The presence of a casing on the burster explosive had little influence on the fragmentation behavior. The effect of an air gap between the burster and the aluminum particles was also investigated. The expansion and fracture of the aluminum were compared with the predictions of a multi-material hydrocode which indicated that the first appearance of cracks through the compacted aluminum layer occurred approximately when the release wave reached the inner surface of the compacted powder.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.423
Threshold uncertainty score0.397

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 head0.027
GPT teacher head0.241
Teacher spread0.213 · 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

Citations7
Published2017
Admission routes1
Has abstractyes

Explore more

Same venueAIP conference proceedingsSame topicEnergetic Materials and CombustionFrench-language works237,207