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Gas leakage model of a spacecraft

2025· article· en· W4413786003 on OpenAlexaboutno aff
Cao Xian, Yongzhe Li, Yanbin Dai, Zhigang Feng

Bibliographic record

VenueJournal of Physics Conference Series · 2025
Typearticle
Languageen
FieldEngineering
TopicSpacecraft and Cryogenic Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsSpacecraftLeakage (economics)Environmental scienceAerospace engineeringComputer scienceAstrobiologyEngineeringPhysics

Abstract

fetched live from OpenAlex

Abstract In order to study the gas leakage process of spacecraft when the hole forms due to space debris impact, this paper uses different approximation levels to construct the model from the perspective of macroscopic gas flow. The ideal incompressible gas single outlet model uses Torricelli’s theorem and the ideal gas equation of state to analyse the transient gas flow in the hole by assuming that the instantaneous density of the gas flowing through the hole does not change. On the basis of the incompressible model, the ideal compressible gas single outlet model is solved by considering the compressibility of the gas, and according to the relationship between the flow velocity and pressure in the critical flow state of the gas, combined with the ideal gas equation of state. Based on the area-velocity equation, the ideal compressible gas Laval nozzle model analyses the relationship between pressure, temperature, flow velocity, and other parameters during supersonic flow for the Laval nozzle shape opening. These three models are gradually advanced from simple to complex, from idealized to close to reality, which provides theoretical support for the study of spacecraft air leakage.

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: none
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
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 head0.017
GPT teacher head0.223
Teacher spread0.206 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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