MétaCan
Menu
Back to cohort
Record W2324381607 · doi:10.2514/6.2014-3479

The VINCI Engine Vibration Test campaign

2014· article· en· W2324381607 on OpenAlexaff
Arnaud Sternchüss, Alexina Bossaert, Patrick Manfredi, Noel David, Patrick Alliot, Anton Grillenbeck

Bibliographic record

Venue50th AIAA/ASME/SAE/ASEE Joint Propulsion Conference · 2014
Typearticle
Languageen
FieldEngineering
TopicRocket and propulsion systems research
Canadian institutionsSafran Electronics (Canada)
Fundersnot available
KeywordsTest (biology)VibrationAutomotive engineeringComputer scienceEngineeringAeronauticsAcousticsPhysicsGeology

Abstract

fetched live from OpenAlex

The VINCI® Engine is the newly developed expander-cycle engine for future European launcher upper stages. This paper takes place in the series of AIAA publications that started on the early VINCI® Engine design. The present paper reports on the engine dynamic characterization which constitutes a major milestone before entering the qualification phase of the engine. This presentation details the present engine development status and the chosen dynamic characterization approach with respect to the programmatic objectives. Specific aspects of the planning and preparation work for the engine vibration test campaign are addressed. Finally, main results and their use for the forthcoming engine qualification activities are highlighted.

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)0.000
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 score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.002

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 head0.025
GPT teacher head0.238
Teacher spread0.213 · 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
Published2014
Admission routes1
Has abstractyes

Explore more

Same venue50th AIAA/ASME/SAE/ASEE Joint Propulsion ConferenceSame topicRocket and propulsion systems researchFrench-language works237,207