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Record W2560871744 · doi:10.1515/ijnsns-2012-0018

Boiling Shocks and Self-Oscillations in Critical Nozzle Flow

2012· article· en· W2560871744 on OpenAlexaboutno aff
O.E. Ivashniov, Marina N. Ivashneva

Bibliographic record

VenueInternational Journal of Nonlinear Sciences and Numerical Simulation · 2012
Typearticle
Languageen
FieldEngineering
TopicRocket and propulsion systems research
Canadian institutionsnot available
Fundersnot available
KeywordsBoilingMechanicsBreakupVaporizationBubbleNozzleShock waveThermodynamicsShock (circulatory)Flow (mathematics)Materials sciencePhysics

Abstract

fetched live from OpenAlex

Abstract Experiments on the depressurization of high-pressure vessels have shown the vaporization to occur in ‘boiling shocks’ moving with the velocity of ∼10 m s−1. This phenomenon was explained by proposing a boiling liquid model accounting for bubble fragmentation. It was shown that an explosive boiling-up was caused by a sharp increase in the interphase area due to a chain process of bubble breakup. In the present study, we use this model, with no change in its free parameters, to simulate the flow in a Laval nozzle. In a critical nozzle flow, boiling occurs to proceed in a shock-type wave as well. It is shown that the formation of boiling shocks may cause autovibrations. The investigation of the shock structure shows that the fulfillment of two conditions is necessary for its realization: Weber number must reach its critical value and the flow velocity must be less than an equilibrium speed of sound. When the conditions cannot be simultaneously realized at a steady-state regime, the flow goes over into a self-oscillation mode.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
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 studies0.0000.001
Scholarly communication0.0000.000
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 head0.042
GPT teacher head0.379
Teacher spread0.337 · 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
Published2012
Admission routes1
Has abstractyes

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