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Record W1979692652 · doi:10.2514/2.1328

Almost-Sure Stochastic Stability of Viscoelastic Plates in Supersonic Flow

2001· article· en· W1979692652 on OpenAlexafffund
Samuel T. Ariaratnam, N. M. Abdelrahman

Bibliographic record

VenueAIAA Journal · 2001
Typearticle
Languageen
FieldEngineering
TopicStability and Controllability of Differential Equations
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsSupersonic speedLyapunov exponentMathematicsStability (learning theory)Flow (mathematics)ViscoelasticityAerodynamicsMechanicsChoked flowMathematical analysisPhysicsNonlinear systemComputer scienceThermodynamics

Abstract

fetched live from OpenAlex

The dynamic stability of a viscoelastic plate in a supersonic gas flow and subjected to a stochastically fluctuating axial thrust is performed within the concept of the Lyapunov exponent. The constitutive relation is modeled in an integral form by using the Boltzmann superposition principle. The piston theory as a quasi-first-order approximation is used to represent the aerodynamic loading on the plate. The stochastic averaging method is used and the Khasminskii's technique [Khasminskii, R. A., Necessary and Sufficient Conditions for the Asymptotic Stability of Linear Stochastic System, Theory of Probability and Its Application, Vol. 12, No. 1, 1967, pp. 144-147 (English translation)] is employed to obtain the stability boundaries. The influence of the various plate and flow parameters and the random loading spectral densities on the stability are investigated.

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)0.003
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 score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.000
Science and technology studies0.0000.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.209
Teacher spread0.196 · 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

Citations24
Published2001
Admission routes2
Has abstractyes

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