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Record W7949700

Feasibility of Developing a Refrigerant-Based Propulsion System for Small Spacecraft

2007· article· en· W7949700 on OpenAlexaff
Carl Seubert, Shawn William Miller, Joseph R. Siebert, Abbie Stewart, Henry J. Pernicka, Refugio Molina, Glenn Lightsey, Megan Sheridan, Brian McDaniels, Graham Walker, Michael Swartwout, Scott Franke

Bibliographic record

VenueJournal of Spinal Disorders · 2007
Typearticle
Languageen
FieldEngineering
TopicSpacecraft and Cryogenic Technologies
Canadian institutionsLockheed Martin (Canada)
Fundersnot available
KeywordsPropulsionPropellantRefrigerantSpacecraftAerospace engineeringSpacecraft propulsionIn-space propulsion technologiesEngineeringAeronauticsSystems engineering
DOInot available

Abstract

fetched live from OpenAlex

This paper documents the feasibility of developing a low pressure, low-budget, two-phase refrigerant propulsion system for small spacecraft. The spacecraft design teams at the University of Missouri-Rolla, University of Texas at Austin, and Washington University in St Louis have collaboratively researched and assessed the feasibility of using a refrigerant propellant to provide a safe and practical type of propulsion system for the small spacecraft community. As an alternative to a typical inert cold-gas system, the teams investigated two-phase refrigerant-based systems motivated by the excellent propellant storage advantages and the ease of use and inherent safety. A primary benefit is its ability to be stored as a saturated liquid with inherently lower pressures as the constant volume system maintains self-equilibrium at saturation pressure. The associated laboratory safety of using a refrigerant propellant and ease of constructing cold-gas hardware make the propulsion system an ideal choice for low-budget satellite developers. The safety and performance analysis conducted on a general system indicates that with appropriate precautions and conservative design, test and analysis a refrigerant-based propulsion system can be safely implemented on small spacecraft and is a viable propulsion option. This feasibility study has been used as a guide to design and develop propulsion systems for each of the universities.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

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 science0.0000.000
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 head0.027
GPT teacher head0.269
Teacher spread0.242 · 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

Citations1
Published2007
Admission routes1
Has abstractyes

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