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Record W2963687790 · doi:10.1002/prep.201800383

Determination of a Measure of Sensitivity to Shock Detonate an Explosive as a Function of its Shock Parameters

2019· article· en· W2963687790 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePropellants Explosives Pyrotechnics · 2019
Typearticle
Languageen
FieldEngineering
TopicEnergetic Materials and Combustion
Canadian institutionsDefence Research and Development Canada
Fundersnot available
KeywordsExplosive materialDetonationShock (circulatory)MechanicsMaterials scienceSensitivity (control systems)Detonation velocityDeflagration to detonation transitionThermodynamicsShock waveChemistryPhysics

Abstract

fetched live from OpenAlex

Abstract The sensitivity of an explosive to detonate due to a shock stimulus is examined using the shock Hugoniots of the condensed material and the detonation products. Explicit equations were developed for the initiation and detonation pressures as a function of the shock parameters, the density, the detonation velocity and the Chapman‐Jouguet pressure which in itself is a function of the heat of detonation. We came upon defining a pressure difference, , between the initiation and detonation pressures which appears to provide a measure of the sensitivity of the explosive to detonate due to a shock loading. For a number of explosives for which reliable shock parameters were available, our results compared very well with widely used and tested small and large scale gap test results. We demonstrated that no one parameter such as the heat of detonation, the Chapman‐Jouguet pressure or even the detonation velocity could be used as a measure of sensitivity to shock detonation but it is the net effect captured by all the parameters that provides the sensitivity of the explosive.

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.

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 score0.013
Threshold uncertainty score0.791

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 head0.017
GPT teacher head0.217
Teacher spread0.201 · 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