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Record W2045980217 · doi:10.5589/q02-018

CFD Analysis for Simulated Altitude Testing of Rocket Motors

2002· article· en· W2045980217 on OpenAlexvenueno aff
Tanguturi Satyanarayana, K. Annamalai, Kishore Visvanathan, V. Babu, T. Sundararajan

Bibliographic record

VenueCanadian aeronautics and space journal · 2002
Typearticle
Languageen
FieldEngineering
TopicRocket and propulsion systems research
Canadian institutionsnot available
Fundersnot available
KeywordsDiffuser (optics)Rocket (weapon)Rocket engineAerospace engineeringNozzleEngineeringRocket engine nozzleVacuum chamberComputational fluid dynamicsMach numberCombustion chamberMechanical engineeringFlight testChamber pressureSimulationMechanicsPhysicsCombustionOptics

Abstract

fetched live from OpenAlex

This paper deals with the high-altitude simulation and testing of upper stage rocket motors with large-nozzle area ratios, using second-throat exhaust diffusers (STED). To evaluate the performance of such motors, the low-pressure environment of the flight situation has to be simulated in the ground-testing installation. The shock pattern developed outside the rocket nozzle in the diffuser system can effectively seal the vacuum test chamber and maintain the required low-vacuum condition in the test chamber. An attempt has been made, in the present study, to numerically compute the flow field in a STED coupled with a large vacuum chamber, for simulating the entire high-altitude-test configuration of a rocket motor. Simulations have been carried out for both cold- and hot-flow situations and for cases with and without a large vacuum chamber. The computational results compare favorably with available experimental results for both hot (γ = 1.2)-flow and cold (γ = 1.4)-flow situations. The operational characteristics of the STED system and the associated flow structure are discussed in 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 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 score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0030.000

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 head0.048
GPT teacher head0.243
Teacher spread0.195 · 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

Citations29
Published2002
Admission routes1
Has abstractyes

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Same venueCanadian aeronautics and space journalSame topicRocket and propulsion systems researchFrench-language works237,207