MétaCan
Menu
Back to cohort
Record W3124074688 · doi:10.13009/eucass2017-64

A numerical analysis of aluminum droplet combustion driven instabilities in solid rocket motors

2017· preprint· en· W3124074688 on OpenAlex
Aurélien Genot, Stany Gallier, Thierry Schuller

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

VenueHAL (Le Centre pour la Communication Scientifique Directe) · 2017
Typepreprint
Languageen
FieldEngineering
TopicRocket and propulsion systems research
Canadian institutionsSafran Electronics (Canada)
FundersCentre National d’Etudes Spatiales
KeywordsMechanicsCombustionOscillation (cell signaling)InstabilitySolid-fuel rocketRocket (weapon)AmplitudeMaterials sciencePhysicsPropellantChemistryAerospace engineeringEngineeringOptics

Abstract

fetched live from OpenAlex

Acoustic coupling with unsteady aluminum particle combustion may lead to self-sustained instabilities with large oscillation amplitudes in a solid rocket motor. A numerical analysis of this phenomenon is carried out for instabilities and at instability limit cycles in a set of generic configurations. It is found that the synchronized combustion oscillations can be split in two different contributions to heat release disturbances driving the instability. In the combustion volume, volumetric heat release rate fluctuations result from the cumulative contribution of burning rate oscillations of each individual aluminum droplet experiencing an oscillating drag. The second contribution to heat release oscillations in the SRM corresponds to the motion of the aluminum combustion zone boundary. In the configurations explored, this contribution may reach up to about 40% of the total heat release rate oscillation in the motor and is shown to depend on the way the end life of aluminum droplets is modeled.

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)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.731
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.020
GPT teacher head0.265
Teacher spread0.244 · 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