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Record W4245056280 · doi:10.22215/etd/2018-12691

Sounding Rocket Roll Control Through DBD Plasma Actuator Boundary Layer Control

2018· dissertation· en· W4245056280 on OpenAlexaff
Spencer Sumanik

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldEngineering
TopicPlasma and Flow Control in Aerodynamics
Canadian institutionsCarleton University
Fundersnot available
KeywordsPlasma actuatorBoundary layerFreestreamActuatorDielectric barrier dischargeSounding rocketAerospace engineeringChord (peer-to-peer)MechanicsFlow control (data)Boundary layer controlBoundary layer thicknessPlasmaMaterials scienceRocket (weapon)Reynolds numberControl theory (sociology)PhysicsEngineeringElectrical engineeringComputer scienceTurbulence

Abstract

fetched live from OpenAlex

Dielectric Barrier Discharge (DBD) plasma actuators induce a plasma flow that alters the velocity of the surrounding air across a surface.The induced flow, directed tangential to the surface, inputs momentum to the boundary layer.This analysis examines the feasibility of a simplified boundary condition within computational fluid dynamic (CFD) simulations of a DBD plasma actuator mounted on a rocket fin.The simulations examine the location of the plasma actuator through a range of freestream velocities.Resulting in a plasma actuator location between 40% and 45% of the fin chord producing the most force.With the actuator at 50% chord a velocity range between 10 and 90 m/s is tested.The highest normal force experienced by the fin due to plasma actuation is approximately 5.5 mN/m at a freestream 70 m/s decreasing as the rocket decelerates.This force and the resulting torque induces an angular velocity of 2.86 RPM of roll on a sounding rocket.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.006

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.008
GPT teacher head0.226
Teacher spread0.218 · 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

Citations0
Published2018
Admission routes1
Has abstractyes

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