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Record W3094128682 · doi:10.1088/1361-6463/abc3ea

Shock waves in pulsed electrical discharges in liquids: numerical simulation and comparison to experiment

2020· article· en· W3094128682 on OpenAlexaff
F.J. Jiménez, Marjan Radfar, Braedan Kirk, R. D. Sydora, Trent S Hunter

Bibliographic record

VenueJournal of Physics D Applied Physics · 2020
Typearticle
Languageen
FieldEngineering
TopicCombustion and Detonation Processes
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMechanicsComputational fluid dynamicsPulsed powerShock wavePlasmaPlasma channelInductorShock (circulatory)CapacitorResistorMaterials scienceVoltageChemistryPhysicsPower (physics)ThermodynamicsElectrical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract In this paper a computational model for the post-breakdown phase of an electrical discharge in liquids is presented and validated through comparison with data from a high voltage pulsed power discharge in a water-filled crucible. The numerical framework consists of an arc plasma channel modeled by equivalent resistor-inductor-capacitor circuit equations coupled to a computational fluid dynamics (CFD) model (based on OpenFOAM) that solves the compressible fluid equations for describing the shock waves associated with the rapid development of the plasma channel. The circuit model equations evolve the initial discharge plasma expansion which are then used to initialize the pressure pulse in the CFD model. Both single-phase (liquid) and two-phase (gas–liquid) CFD solvers were implemented and compared. The dynamics and magnitude of the simulated pressure pulse perturbations at the boundaries of the crucible were validated with the pressure sensor measurements made in an experiment of a pulsed electrical discharge in liquid water.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.264
Threshold uncertainty score0.513

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.025
GPT teacher head0.285
Teacher spread0.260 · 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 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

Citations9
Published2020
Admission routes1
Has abstractyes

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