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Record W4317634762 · doi:10.2514/6.2023-2186

Investigation of Baffled-Tube Ram Accelerator Configurations

2023· article· en· W4317634762 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

VenueAIAA SCITECH 2023 Forum · 2023
Typearticle
Languageen
FieldEngineering
TopicRocket and propulsion systems research
Canadian institutionsMcGill University
Fundersnot available
KeywordsBaffleProjectileThrustPropellantMach numberAerospace engineeringMechanicsTube (container)Adiabatic processMaterials scienceHypersonic speedNuclear engineeringPhysicsMechanical engineeringEngineeringThermodynamics

Abstract

fetched live from OpenAlex

View Video Presentation: https://doi.org/10.2514/6.2023-2186.vid The ram accelerator is a combustion driven launch system designed to accelerate projectiles to hypersonic velocities. To improve performance and extend operability limits, the baffled tube ram accelerator (BTRA) was developed, utilizing a series of washer-like baffles with axisymmetric projectiles. This work presents the results from an experimental investigation on the influences of propellant chemistry, pressure staging, baffle configuration, and projectile geometries on thrust characteristics of the BTRA. Thrust was found to scale with heat release in a methane-air-diluent mixture, and to scale proportionally with tube fill pressure. Increased baffle chamber diameter was found to have a detrimental effect on thrust performance, while increased projectile length resulted in an increase in thrust at any given fill pressure. Continuous operation was demonstrated in an 8-m-long BTRA over the velocity range of 0.7 km/s to 1.4 km/s and Mach numbers of 2.0 to 4.2. The upper Mach number limit to BTRA operation has not yet been determined.

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 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 score0.251
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.045
GPT teacher head0.281
Teacher spread0.235 · 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