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Record W2059737095 · doi:10.2514/1.j053790

Development of a Short-Duration Rocket Nozzle Flow Simulation Facility

2015· article· en· W2059737095 on OpenAlexaboutno aff
G. Yahiaoui, H. Olivier

Bibliographic record

VenueAIAA Journal · 2015
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsnot available
FundersDeutsche Forschungsgemeinschaft
KeywordsNozzleRocket engine nozzleRocket (weapon)Rocket engineAerospace engineeringFlow (mathematics)Mechanical engineeringMass flowDischarge coefficientCombustionReal gasEngineeringMechanicsNuclear engineeringPhysicsChemistry

Abstract

fetched live from OpenAlex

The rising demand for reliable wind-tunnel flow data for rocket nozzle design applications led to the development of a new type of facility. Most of the former experimental data in the literature were gathered in conditions far from those encountered in real engines and combustion gas generators. Thus, they are not appropriate for the physical interpretation of complex flow phenomena and computational fluid dynamic tools validation. The new experimental platform is intended to solve this problem by its capability to nearly match most of these conditions. It allows for the investigation of several engine-relevant aerothermodynamic problems such as boundary-layer transition, nozzle flow separation, nozzle exhaust plume interactions, etc. Furthermore, innovative nozzle cooling techniques like film cooling can be studied in this new type of facility. This is demonstrated first by the experimental results given at the end of this paper. High nozzle reservoir pressures and temperatures are achieved by means of detonative combustion of a premixed gas in a confined tube. A detonation wave produces a high-energy flow that expands through a Laval nozzle to the desired experimental flow conditions. The facility simulates enginelike conditions in a combustion environment for various mass ratios of oxidizer–fuel mixtures. The short-duration flow device affords a simple and cost-effective research tool for testing under harsh flow conditions in laboratories. Hence, it will significantly contribute to the understanding of complex rocket nozzle flow phenomena and validation of numerical tools, as well as correlations.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.464
Threshold uncertainty score0.226

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.051
GPT teacher head0.276
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.

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

Citations8
Published2015
Admission routes1
Has abstractyes

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