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Record W2380664619

Fluid mechanics behaviors in gas explosion

2009· article· en· W2380664619 on OpenAlexaboutno aff
Gao Jian-kang

Bibliographic record

VenueMeitan xuebao · 2009
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsnot available
Fundersnot available
KeywordsTurbulenceNozzleMechanicsShock waveFlow (mathematics)AccelerationFlame speedShock (circulatory)Fluid mechanicsMaterials scienceChemistryPhysicsPremixed flameCombustionThermodynamicsClassical mechanics
DOInot available

Abstract

fetched live from OpenAlex

The effects on flame propagation and explosion wave caused by the wall roughness and pipeline changing in gas explosion were examined experimentally: flame speed grew from 275.1 m/s to 580.26 m/s sharply when the wall roughness changed from 2 mm to 4 mm,then droped to 369.05 m/s when the wall roughness changed to 6 mm.When the pipeline area expanded or reduced suddenly,the flame speed rapidly increased from 15.2 m/s(L/D=16) to 1 287.7 m/s(L/D=165).The different performance of the flame speed which caused by the turbulent flow in these two kinds of pipeline also were theoretically studied.The fluid mechanics behaviors in gas explosion,such as the turbulent flow,the shock wave,the friction pipe flow and the Laval nozzle effect,were analyzed.The results indicate that the turbulent flow caused by the wall roughness and the pipeline area can lead to the flame speed raised largely,but the turbulent flow only is a secondary factor which induced the flame acceleration,the Laval nozzle effect is basic factor which caused the flame acceleration,the gas explosion intensity aggravating.

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 score0.002
Threshold uncertainty score0.003

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 communication0.0000.000
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 head0.009
GPT teacher head0.221
Teacher spread0.212 · 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

Citations0
Published2009
Admission routes1
Has abstractyes

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