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Record W6968460700 · doi:10.5281/zenodo.15839418

Prediction of the critical tension required for cavitation onset in transient pressure fields

2025· dataset· en· W6968460700 on OpenAlexaff

Bibliographic record

VenuePolyPublie (École Polytechnique de Montréal) · 2025
Typedataset
Languageen
FieldMaterials Science
TopicUltrasound and Cavitation Phenomena
Canadian institutionsPolytechnique Montréal
Fundersnot available
KeywordsCavitationDimensionless quantityBubbleCritical radiusRADIUSWork (physics)Surface tension

Abstract

fetched live from OpenAlex

The following repository contains the relevant data and code used to produce the results presented in our upcoming paper. Our work is about the phenomenon of cavitation onset. We propose a precise definition of cavitation onset and characterize the pressure conditions required for cavitation onset to occur in transient pressure fields. In this study, we consider the case of a single gas bubble in a Newtonian liquid whose radial dynamics are modeled using the Keller-Miksis equation (Keller and Miksis 1980). The bubble is subjected to a single tension pulse considered as a canonical transient pressure field. The repository consists of: A first dataset, Data_Section4_SelfSimilarity.txt. Given a properly built dimensionless framework, our work highlights that cavitation onset in a transient pressure field is self-similar. The definition of the dimensionless framework is detailed in the upcoming paper associated to this Zenodo repository. This dataset contains for a set of dimensionless parameters the critical tension ratio required to observe cavitation onset and the normalized maximum radius reached by the bubble when applying the critical tension ratio. Self-similarity of cavitation onset is validated by imposing a specific value of the initial bubble radius and adapting the values of the other characteristic variables representing the gas-liquid system to match the desired set of dimensionless numbers. The results obtained with the dimensionless framework are unaffected by the choice of the initial bubble radius. A second dataset, Data_Section5_OnsetInLiquids.txt. This dataset contains, for three different liquids (water, aluminium and ethanol), the critical tension required to observe cavitation onset (in Pa) and the maximum radius reached by the bubble when applying the critical tension (in m), depending on the initial size of the bubble (in m) and the duration of the tension pulse (in s). We highlight that only the pairs of parameters (initial bubble size, duration of the pulse) for which the negative pressure/tension required for cavitation onset is above the fracture pressure of the liquid, estimated by nucleation theory (Fisher 1948), are stored in this dataset. A code written in C located in the subfolder Code_CriticalTension. The aim of this code is to obtain for a given set of properties describing the gas-liquid system (density, initial size of the bubble...) indicated by the user the critical tension required for cavitation onset and the maximum radius reached by the bubble when applying the critical tension. All details on how to use the code are given in the README.md file located in the subfolder.

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)0.001
metaresearch head score (Gemma)0.006
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: Dataset · Consensus signal: Dataset
Teacher disagreement score0.008
Threshold uncertainty score0.027

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.006
Meta-epidemiology (narrow)0.0020.000
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.003
Science and technology studies0.0000.000
Scholarly communication0.0020.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0080.009

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 head0.255
Teacher spread0.241 · 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
GenreDataset

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
Published2025
Admission routes1
Has abstractyes

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