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Record W4284672536 · doi:10.1017/jfm.2022.513

Wavenumber lock-in and spatial parametric resonance in convection

2022· article· en· W4284672536 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueJournal of Fluid Mechanics · 2022
Typearticle
Languageen
FieldComputer Science
TopicNonlinear Dynamics and Pattern Formation
Canadian institutionsWestern University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsWavenumberConvectionPrandtl numberInstabilityPhysicsRayleigh numberResonance (particle physics)WavelengthMechanicsNatural convectionAtomic physicsOptics

Abstract

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Analysis of convection driven by spatial periodic heating shows a wealth of responses due to Prandtl number dependence. The primary convection is delineated by the heating wavenumber and the secondary convection is characterized by the critical wavenumber established by an instability process. The resulting two-wavenumber dynamical system involves spatial parametric resonance leading to the wavenumber lock-in and the Rayleigh–Bénard (RB) instability producing unlocked states. Heating conditions leading to the co-existence of both types of states have been identified. Transition from the locked to the unlocked states produces states with a wide range of wavelengths and diverse patterns of movement. The possible secondary states are driven by a competition between the RB mechanism and the spatial parametric resonance. The relative strengths of these mechanisms change with Prandtl number $Pr$ resulting in four types of system responses. In the type A response occurring for $Pr>0.4$ , parametric resonance dominates for the heating wavenumber $\alpha < 4.5$ resulting in the pattern lock-in between the primary and secondary convections whereas RB occurs for $\alpha > 10$ . There is a wealth of possible convection patterns in the in-between zone where a small change of $\alpha$ results in a major change of flow pattern. In the type B response, which occurs for $0.19< Pr< 0.4$ , the RB effect dominates eliminating the lock-in. The type C response, which occurs for $0.08 < Pr< 0.19$ , is similar to type A but stronger spatial modulation extends the range of dominance of parametric resonance up to $\alpha =7$ while the RB effect dominates for $\alpha >10$ as in the type A response. A wealth of possible patterns occurs in the transition zone ( $7<\alpha <10$ ). In the type D response, which occurs for $Pr<0.08$ , the strong spatial modulation results in the formation of two separate critical stability curves, one resulting from the dominance of the spatial parametric resonance leading to the lock-in effect, and the other one corresponding to the dominance of the RB effect producing unlocked states. No continuous transition between both states can occur. Conditions where both distinct states can arise simultaneously were identified. Morphing between different patterns of secondary convection may occur in response to small changes in the heating pattern in types A and C, while such processes are not possible in types B and D.

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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)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.949
Threshold uncertainty score0.192

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.220
Teacher spread0.211 · 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