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Record W1965857624 · doi:10.5589/q03-902

Erratum: CFD Analaysis for Simulated Altitude Testing of Rocket Motors

2003· erratum· en· W1965857624 on OpenAlexvenueno aff
Tanguturi Satyanarayana, K. Annamalai, Kishore Visvanathan, V. Babu, T. Sundararajan

Bibliographic record

VenueCanadian aeronautics and space journal · 2003
Typeerratum
Languageen
FieldEngineering
TopicRocket and propulsion systems research
Canadian institutionsnot available
Fundersnot available
KeywordsComputational fluid dynamicsAeronauticsRocket (weapon)Aerospace engineeringAltitude (triangle)EngineeringMeteorologyMarine engineeringEnvironmental sciencePhysicsMathematics

Abstract

fetched live from OpenAlex

RESUME La presente communication porte sur l’essai et la simulation en haute altitude des moteurs-fusees d’etage superieur a grands rapports de surface au moyen de diffuseurs d’echappement presentant un deuxieme venturi (STED). Pour evaluer le rendement de ces moteurs, il faut simuler un environnement basse pression de la situation de vol dans une installation d’essai au sol. L’onde de choc qui se developpe a l’exterieur de la tuyere du moteur dans le diffuseur peut effectivement etancher la chambre d’essai sous vide et maintenir le vide peu pousse necessaire dans cette chambre. Dans la presente etude, on a tente de calculer numeriquement le champ d’ecoulement dans un diffuseur d’echappement presentant un deuxieme venturi, couple a une chambre dans laquelle regnait un vide pousse pour simuler toute la configuration d’essais en haute altitude d’un moteur-fusee. Les simulations ont ete executees pour des ecoulements chauds et froids et pour des cas avec et sans une grande chambre sous vide. Les resultats de calcul se comparent avantageusement aux resultats experimentaux disponibles pour des ecoulements chauds ( = 1,2) et froids ( = 1,4). Les caracteristiques operationnelles du systeme STED et la structure de l’ecoulement connexe sont traites en detail.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.397
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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

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 head0.029
GPT teacher head0.254
Teacher spread0.225 · 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 teacher head, not a consensus.

Study designNot applicable
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
Published2003
Admission routes1
Has abstractyes

Explore more

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