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Record W2955569070 · doi:10.1063/1.5093028

Shock wave induced cavitation of silicone oils

2019· article· en· W2955569070 on OpenAlexafffund

Bibliographic record

VenueJournal of Applied Physics · 2019
Typearticle
Languageen
FieldMaterials Science
TopicUltrasound and Cavitation Phenomena
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsCavitationSilicone oilSurface tensionSpallShock (circulatory)Shock waveStrain rateRheologyViscosityPropellant

Abstract

fetched live from OpenAlex

The cavitation threshold of polydimethylsiloxane (silicone) oils was studied using the planar impact of flyer plates to generate large transient negative pressures within the liquids. The plate-impact experiments used a 64-mm-bore gas-gun to launch thin sabot-supported flyer plates onto liquid capsule targets in which a thin Mylar diaphragm formed a free surface at the back of the sample. The shock wave driven into the target capsule by the flyer impact placed the silicone oil in tension upon reflection from the rear free surface, eventually causing the sample to cavitate. The spall strength, or critical tension which cavitates the liquid, was determined by monitoring the free-surface velocity using a photonic Doppler velocimetry system. This study explored the effect of viscosity and loading strain rate on a system of three silicone oils having vastly different viscosities (4.8×10−2Pas to 2.9×101Pas), but otherwise similar properties. The spall strength was found to remain constant over the ranges of strain rate and viscosities probed in this work. A comparison of the experimental results to models for the cavitation threshold of liquids suggested that homogeneous nucleation of bubbles was the dominant mechanism for tension relief at the onset of cavitation.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.281

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.016
GPT teacher head0.234
Teacher spread0.218 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations4
Published2019
Admission routes2
Has abstractyes

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