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Record W2387615463

Influence of Pressure Ratios on Cold Gas Flow Field in HV SF_6 Circuit Breaker Nozzles

2012· article· en· W2387615463 on OpenAlexaboutno aff
Su Na

Bibliographic record

VenueXi'an Jiaotong Daxue xuebao · 2012
Typearticle
Languageen
FieldPhysics and Astronomy
TopicVacuum and Plasma Arcs
Canadian institutionsnot available
Fundersnot available
KeywordsNozzleMach numberMechanicsOverall pressure ratioShock (circulatory)Circuit breakerDischarge coefficientChoked flowPressure measurementInletFlow (mathematics)Supersonic speedMaterials scienceChemistryThermodynamicsPhysicsElectrical engineeringMechanical engineeringGas compressorEngineering
DOInot available

Abstract

fetched live from OpenAlex

Cold SF6 gas flow field is calculated and analyzed for three kinds of Laval nozzle structures to guide thermal gas flow field simulation in high voltage circuit breakers.The influences of different nozzle length,upstream and downstream pressures are investigated by comparing the variety characteristics of the pressure and the Mach number.The critical pressure values of the three nozzle structures are confirmed.The relationship between shock initiation and pressure ratio is analyzed,and the calculation error caused by available plasma properties data is discussed.The results show that different length nozzle structures are with different critical pressure values.The shocks appear when the pressure ratio is lower than the critical value,otherwise no shock arising.Shock position varies with the pressure ratio and nozzle length.The outlet pressure is independent on the setting value and increases with the inlet pressure when the gas flow velocity gets always supersonic along in the nozzle downstream.The error in the simulation can be reduced with the effective implementation of the gas properties,which may improve the accuracy of the calculation results.

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)0.000
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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.233
Teacher spread0.222 · 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

Citations5
Published2012
Admission routes1
Has abstractyes

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