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Record W2377449772

Numerical simulation of swirling flow characteristics of supersonic swirling natural gas separator

2007· article· en· W2377449772 on OpenAlexaboutno aff
Lin Zong-hu

Bibliographic record

VenueZhongguo Shiyou Daxue xuebao. Ziran kexue ban · 2007
Typearticle
Languageen
FieldEngineering
TopicRocket and propulsion systems research
Canadian institutionsnot available
Fundersnot available
KeywordsSupersonic speedChoked flowSeparator (oil production)MechanicsMach numberSupersonic wind tunnelNozzleCyclonic separationWingChemistryAerospace engineeringPhysicsThermodynamicsEngineeringMechanical engineering
DOInot available

Abstract

fetched live from OpenAlex

Supersonic swirling natural gas separator is a revolutionary gas conditioning technology compared with traditional low-temperature separation.In supersonic swirling separator,while the gas stream passing through Laval nozzle,the gas stream forms supersonic low-temperature stream with small liquid droplets because of adiabatic expansion effect of nozzle.The gas mixture enters the wing section and turns into swirling flow from axial flow by the action of supersonic wing,and then gas and condensed liquid drops are separated in the drainage section.The supersonic wing is a key component of supersonic swirling separator.Deltaic plate supersonic wing was designed.By using CFD software,the supersonic swirling flow field was studied,and the distributions of the temperature,pressure,Mach number in the wing section and tangential velocity along longitudinal section were analyzed.Supersonic swirling characteristics of gas in the wing section were determined.The results show that the gas in the supersonic wing section can always maintain supersonic velocity.The Mach number in the wing section outlet is 1.4 and there is no shock wave before the wing section.The maximum swirling accleration is 572 000 g.The gas-liquid separation of supersonic gas can be realized well.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.574
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
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.016
GPT teacher head0.276
Teacher spread0.260 · 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

Citations2
Published2007
Admission routes1
Has abstractyes

Explore more

Same venueZhongguo Shiyou Daxue xuebao. Ziran kexue banSame topicRocket and propulsion systems researchFrench-language works237,207