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Record W2014980001 · doi:10.2514/1.b35289

Investigation on Hypersonic Inlet Starting Process in Continuous Freejet Wind Tunnel

2014· article· en· W2014980001 on OpenAlexaboutno aff
Yi Wang, Zhenguo Wang, Jianhan Liang, Xiaoqiang Fan

Bibliographic record

VenueJournal of Propulsion and Power · 2014
Typearticle
Languageen
FieldEngineering
TopicComputational Fluid Dynamics and Aerodynamics
Canadian institutionsnot available
FundersNational University of Defense TechnologyNational Natural Science Foundation of China
KeywordsScramjetAeronauticsAerospace engineeringHypersonic speedSupersonic speedAstronauticsEngineeringWind tunnelCombustor

Abstract

fetched live from OpenAlex

No AccessTechnical NoteInvestigation on Hypersonic Inlet Starting Process in Continuous Freejet Wind TunnelYi Wang, Zhenguo Wang, Jianhan Liang and Xiaoqiang FanYi WangScience and Technology on Scramjet Laboratory, National University of Defense Technology, 410073 Changsha, People's Republic of China, Zhenguo WangScience and Technology on Scramjet Laboratory, National University of Defense Technology, 410073 Changsha, People's Republic of China, Jianhan LiangScience and Technology on Scramjet Laboratory, National University of Defense Technology, 410073 Changsha, People's Republic of China and Xiaoqiang FanScience and Technology on Scramjet Laboratory, National University of Defense Technology, 410073 Changsha, People's Republic of ChinaPublished Online:20 Oct 2014https://doi.org/10.2514/1.B35289SectionsRead Now ToolsAdd to favoritesDownload citationTrack citations About References [1] Mahoney J., Inlets for Supersonic Missiles, AIAA Education Series, AIAA, New York, 1990, p. 1. Google Scholar[2] Curran E. and Murthy S., Scramjet Propulsion, Vol. 189, Progress in Astronautics and Aeronautics, AIAA, Reston, VA, 2000, p. 449. Google Scholar[3] Van Wie D., Kwok F. and Walsh R., "Starting Characteristics of Supersonic Inlets," AIAA Paper 1996-2914, 1996. LinkGoogle Scholar[4] Hawkins W. and Marquart E., "Two-Dimensional Generic Inlet Unstart Detection at Mach 2.5–5.0," AIAA Paper 1995-6019, 1995. LinkGoogle Scholar[5] Vinogradov V., Stepanov V. and Goldfeld M., "Experimental and Numerical Investigation of Two Concepts of the Hypersonic Inlet," AIAA Paper 1995-2721, 1995. LinkGoogle Scholar[6] Smart M., Trexler C. and Goldman A., "A Combined Experimental/Computational Investigation of Rocket Based Combined Cycle Inlet," AIAA Paper 2001-0671, 2011. Google Scholar[7] Wagner J., Valdivia A., Yuceil K., Clemens N. T. and Dolling D. S., "An Experimental Investigation of Supersonic Inlet Unstart," AIAA Paper 2007-4352, 2007. LinkGoogle Scholar[8] Falempin F., Wendling E., Goldfeld M., Starov A. and Timofeev K., "Influence of Gas Injection and Combustion on Start and Characteristics of Inlet," AIAA Paper 2008-2514, 2008. LinkGoogle Scholar[9] Lu F. and Marren D., Advanced Hypersonic Test Facilities, Vol. 198, Progress in Astronautics and Aeronautics, AIAA, Reston, VA, 2002, p. 24. Google Scholar[10] McGregor R., Molder S. and Paisley T., "Hypersonic Inlet Flow Starting in the Gun Tunnel," Investigation in the Fluid Dynamics of Scramjet Inlets, Ryerson Polytechnical Inst. and Univ. of Toronto, Canada, July 1992. Google Scholar[11] Fan X., "Design Method, Numerical Simulation and Experimental Research of Hypersonic Inlet," Ph.D. Thesis, National Univ. of Defense Technology, Changsha, PRC, 2006, pp. 79–81 (in Chinese). Google Scholar[12] Voland R., Rock K., Huebner L., Witte D. W., Fischer K. E. and McClinton C. R., "Hyper-X Engine Design and Ground Test Program," AIAA Paper 1998-1532, 1998. LinkGoogle Scholar[13] Wang Y., Liang J., Fan X., Liu W. and Wang Z., "Investigation on the Unstarted Flowfield of a Three-Dimensional Sidewall Compression Hypersonic Inlet," AIAA Paper 2009-7404, 2009. Google Scholar Previous article Next article

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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.009
GPT teacher head0.209
Teacher spread0.201 · 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

Citations16
Published2014
Admission routes1
Has abstractyes

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