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Record W2034340378 · doi:10.2514/6.2012-3227

Evaluation of Drogue Parachute Damping Effects Utilizing the Apollo Legacy Parachute Model

2012· article· en· W2034340378 on OpenAlexaff
Kelly M. Currin, J. D. Gamble, Daniel Matz, David Bretz

Bibliographic record

Venue30th AIAA Applied Aerodynamics Conference · 2012
Typearticle
Languageen
FieldEngineering
TopicAerospace Engineering and Energy Systems
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsApolloAerospace engineeringMoon landingAeronauticsComputer scienceEngineeringGeology

Abstract

fetched live from OpenAlex

Drogue parachute damping is required to dampen the Orion Multi Purpose Crew Vehicle (MPCV) crew module (CM) oscillations prior to deployment of the main parachutes. During the Apollo program, drogue parachute damping was modeled on the premise that the drogue parachute force vector aligns with the resultant velocity of the parachute attach point on the CM. Equivalent Cm(sub q) and Cm(sub alpha) equations for drogue parachute damping resulting from the Apollo legacy parachute damping model premise have recently been developed. The MPCV computer simulations ANTARES and Osiris have implemented high fidelity two-body parachute damping models. However, high-fidelity model-based damping motion predictions do not match the damping observed during wind tunnel and full-scale free-flight oscillatory motion. This paper will present the methodology for comparing and contrasting the Apollo legacy parachute damping model with full-scale free-flight oscillatory motion. The analysis shows an agreement between the Apollo legacy parachute damping model and full-scale free-flight oscillatory motion.

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)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0020.000

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 head0.030
GPT teacher head0.237
Teacher spread0.207 · 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 designSimulation or modeling
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

Citations3
Published2012
Admission routes1
Has abstractyes

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