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Record W2146143078 · doi:10.1017/s002211200999317x

Holmboe wave fields in simulation and experiment

2010· article· en· W2146143078 on OpenAlexaff
Jeffrey R. Carpenter, Edmund W. Tedford, Mona Rahmani, Gregory A. Lawrence

Bibliographic record

VenueJournal of Fluid Mechanics · 2010
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Vibration Analysis
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsWavenumberPhysicsAmplitudeVortexWavelengthMechanicsInstabilityDirect numerical simulationPairingClassical mechanicsOpticsCondensed matter physicsTurbulence

Abstract

fetched live from OpenAlex

The basic wave field resulting from Holmboe's instability is studied both numerically and experimentally. Comparisons between the direct numerical simulations (DNS) and laboratory experiments result in Holmboe waves that are similar in their appearance and phase speed. However, different boundary conditions result in mean flows that display gradual variations either temporally (in the simulations) or spatially (in the experiments). These differences are found to affect the evolution of the dominant wavenumber and amplitude of the wave field. The simulations exhibit a nonlinear ‘wave coarsening’ effect, whereby the energy is shifted to lower wavenumbers in discrete merging events. This process is typically found to result from either ejections of mixed fluid away from the density interface or vortex pairing. In the experiments, energy is transferred to lower wavenumbers by the ‘stretching’ of the wave field by a gradually varying mean velocity. This stretching results in a reduction of wave amplitude compared with the DNS.

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)0.002
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 score0.003
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.011
GPT teacher head0.238
Teacher spread0.228 · 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

Citations36
Published2010
Admission routes1
Has abstractyes

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