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CFD Simulation of gas flow in a 122 mm supersonic nozzle

2022· article· en· W4312698348 on OpenAlexaboutno aff
Kamonwan Srathonghuam, Adulyasak Boonpan, Jatuporn Thongsri

Bibliographic record

Venue2022 37th International Technical Conference on Circuits/Systems, Computers and Communications (ITC-CSCC) · 2022
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsnot available
Fundersnot available
KeywordsNozzleMach numberSupersonic speedComputational fluid dynamicsMechanicsPropulsionChoked flowRocket engine nozzleAerospace engineeringShock (circulatory)Flow (mathematics)Rocket (weapon)Materials sciencePhysicsEngineering

Abstract

fetched live from OpenAlex

Developing a highly efficient supersonic rocket propulsion system requires understanding gas flow inside a nozzle. In this research, Computational Fluid Dynamics (CFD) was applied to investigate a gas flow behavior of a 122 mm, de Laval nozzle in a steady state. Based on an actual operating condition, CFD results showed the gas flow behavior leading to shock, separation, recirculation, reattachment, Mach number, total temperature, and pressure of the nozzle, consistent with the theory. In addition, the Mach number increases with increasing the nozzle's length, as expected. The results found can be employed to design a new high-efficiency supersonic nozzle.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.442
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.032
GPT teacher head0.265
Teacher spread0.233 · 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 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

Citations1
Published2022
Admission routes1
Has abstractyes

Explore more

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