MétaCan
Menu
Back to cohort
Record W2043689344 · doi:10.1080/10916460701304410

Computational Fluid Dynamics Study for Flow of Natural Gas through High-pressure Supersonic Nozzles: Part 2. Nozzle Geometry and Vorticity

2008· article· en· W2043689344 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePetroleum Science and Technology · 2008
Typearticle
Languageen
FieldMathematics
TopicGas Dynamics and Kinetic Theory
Canadian institutionsMemorial University of Newfoundland
Fundersnot available
KeywordsNozzleMechanicsVorticityShock (circulatory)Supersonic speedInletGeometryComputational fluid dynamicsFlow (mathematics)Materials sciencePhysicsThermodynamicsVortexGeologyMathematics

Abstract

fetched live from OpenAlex

Abstract The computational fluid dynamics technique is used to study the behavior of high-pressure natural gas when it flows through nozzles with supersonic velocities. Effect of nozzle geometry is discussed by inserting a constant area channel between the convergent and divergent parts of the system. Various conduit lengths are analyzed to show how the minimum temperature could be influenced by the geometry of the nozzle. The results also show that changing channel length can affect the position of shockwave. The results for the effect of vorticity on the performance of the nozzles show that, although losses in pressure increase due to inlet swirl flow, vorticity increases very sharply in the vicinity of the shock. It could be concluded that the region just before the shock spot is the main region where fine particles can be separated because of the large vorticity strength. Shock with reasonable strength may be favored in practical applications where fine particles separation is desired.

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.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.584
Threshold uncertainty score0.623

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.002
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 head0.014
GPT teacher head0.264
Teacher spread0.249 · 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