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Record W2337415033 · doi:10.1002/prep.201500246

Validation of the Gurney Model in Planar Geometry for a Conventional Explosive

2016· article· en· W2337415033 on OpenAlexaff
Jason Loiseau, William Georges, Andrew Higgins

Bibliographic record

VenuePropellants Explosives Pyrotechnics · 2016
Typearticle
Languageen
FieldEngineering
TopicEnergetic Materials and Combustion
Canadian institutionsMcGill University
Fundersnot available
KeywordsExplosive materialAccelerationPlanarMechanicsRange (aeronautics)AcousticsOpticsPhysicsAerospace engineeringMaterials scienceEngineeringComputer scienceChemistryClassical mechanics

Abstract

fetched live from OpenAlex

Abstract The analytical model developed by Gurney is a seminal tool for analyzing the acceleration of metal flyers driven by detonating high explosives. Despite the continued relevance of this model, relatively few experimental validations over a wide range of flyer‐to‐charge mass ratios exist in the open literature. The current study presents experimental results for planar aluminum flyers propelled by a conventional explosive over a range of mass ratios varying from 4.65 to 0.03. Flyer velocity was measured via Heterodyne Laser Velocimetry (PDV), permitting a continuous measurement of the acceleration process. Measured flyer velocities are compared to terminal velocity estimations from the Gurney model. Experimental terminal velocities are compared to the open face and asymmetric sandwich Gurney models. Excellent agreement is observed for terminal velocity predictions considering the gasdynamic simplifications inherent in the model formulation.

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 score0.006
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0010.000
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 head0.022
GPT teacher head0.215
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

Citations16
Published2016
Admission routes1
Has abstractyes

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