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Record W4246453896 · doi:10.32920/ryerson.14661933.v1

Effects of Grain Geometry and Vibration on the Suppression of Combustion Instability in a Solid Rocket Motor

2021· preprint· en· W4246453896 on OpenAlexaff
Christopher Baczynski

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicRocket and propulsion systems research
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsSolid-fuel rocketPropellantMechanicsCombustionInstabilityVibrationRocket (weapon)Materials scienceAccelerationPhysicsClassical mechanicsAerospace engineeringAcousticsEngineeringChemistry

Abstract

fetched live from OpenAlex

A comprehensive numerical model for internal ballistic simulation under dynamic flow, combustion and structural vibration conditions is used to investigate the effectiveness of grain port area transitions of a reference solid rocket motor as a means for suppression of axial combustion instability symptoms. Modification of the propellant grain geometry is one of several traditional means for suppressing symptoms in actual motors. With respect to these symptoms, individual transient simulation runs show the evolution of the axial pressure wave and associated DC shift for the given grain geometry, as initiated by a given pressure disturbance. Limit pressure wave magnitudes are collected for a number of simulation runs for different grain area transition positions, steepness and aspect ratios, and mapped on an attenuation trend chart. Effects of acceleration, through structural vibration of the propellant surface, on the combustion process are investigated, and their influence on the effectiveness of grain area transitions is examined. With or without acceleration/vibrations effects included, the numerical results produced in this study confirm the significant ability of a grain area transition to suppress combustion instability symptoms.

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)0.001
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 score0.080
Threshold uncertainty score0.417

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.269
Teacher spread0.252 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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