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Record W7029276424

Impact induced detonation of cased explosive

2013· article· en· W7029276424 on OpenAlexvenueno aff

Bibliographic record

VenueNPARC · 2013
Typearticle
Languageen
FieldEngineering
TopicEnergetic Materials and Combustion
Canadian institutionsnot available
Fundersnot available
KeywordsExplosive materialDetonationShock (circulatory)Shock waveDeflagration to detonation transitionIgnition systemAluminium
DOInot available

Abstract

fetched live from OpenAlex

Fragments of aluminium impacting on Composition B explosives encased in rolled homogenous armour (RHA) steel were investigated using the explicit nonlinear finite element method. The investigation focused on shock to detonation simulations of Composition B, with the objective of determining the critical velocity which would generate a shock wave strong enough to cause detonation of the explosive and the resulting pressure profile of the detonation wave. Detonation scenarios at low, intermediate, high impact velocity were investigated. It was observed that a) at intermediate velocities detonation was due to the development of localized hot spots caused by the compression of the explosive from the initial shockwave; b) at high impact velocity, initiation of the explosive was caused by the initial incident wave behind the top casing/explosive interface. c) At low impact velocity, initiation of the explosive may be caused by the increased pressure of reflecting waves against the surfaces of the explosive casing. This case served to show the importance of capturing all confining surfaces correctly as any surface enhance detonation. Advanced features of the simulation includes Arbitrary-Lagrangian-Eulerian (ALE) approach, the Elastic Plastic Hydrodynamic constitutive material model and the Ignition and Growth of Reaction in High Explosive eq uation of state (IGRHE-EOS) to account for the probability that the explosive may not detonate when impacted.

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 categoriesInsufficient payload (model declined to judge)
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 score0.033
Threshold uncertainty score1.000

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)0.0010.000

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 head0.011
GPT teacher head0.214
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.

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

Citations0
Published2013
Admission routes1
Has abstractyes

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