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DEVELOPMENT OF A PARAFFIN/NITROUS OXIDE HYBRID ROCKET MOTOR FOR FLIGHT-BASED TESTING

2021· article· en· W3135652303 on OpenAlexaff
Colin Hill, Graham Doerksen, Declan Quinn, Craig T. Johansen

Bibliographic record

VenueInternational Journal of Energetic Materials and Chemical Propulsion · 2021
Typearticle
Languageen
FieldEngineering
TopicRocket and propulsion systems research
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsPropellantInjectorAerospace engineeringRocket (weapon)Automotive engineeringCombustionCombustion chamberMaterials scienceEnvironmental scienceProcess engineeringMechanical engineeringEngineeringChemistry

Abstract

fetched live from OpenAlex

A 108 millimeter diameter hybrid motor has been developed using a liquefying paraffin-based fuel and nitrous oxide as the oxidizer. Multiple static test firings have been performed in addition to a successful sounding rocket flight. A number of practical lessons have been learned through the development process relating to injector configuration, regression rate and combustion efficiency. It is identified in the current work that further research is required in the liquefying fuel hybrid rocketry field in order to arrive at a collection of best practices for the design of efficient motors. Two primary concerns identified in this work are the structural properties of the paraffin-based fuel and efficient propellant mixing in the combustion chamber. Addressing these design considerations will be a major component in maturing liquefying hybrid fuels, such as paraffin wax, for use on larger scale vehicles intended for high-altitude or orbital missions.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.024
GPT teacher head0.262
Teacher spread0.238 · 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 source (direct Gemma or distilled Codex), 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

Citations4
Published2021
Admission routes1
Has abstractyes

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