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Record W2038898935 · doi:10.1115/imece2012-89140

Nonlinear Parametric Instability of Functionally Graded Rectangular Plates in Thermal Environments

2012· article· en· W2038898935 on OpenAlexaff
Farbod Alijani, Marco Amabili

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicComposite Structure Analysis and Optimization
Canadian institutionsMcGill University
Fundersnot available
KeywordsNonlinear systemMathematical analysisBoundary value problemInstabilityMathematicsParametric statisticsPhysicsMechanics

Abstract

fetched live from OpenAlex

Geometrically nonlinear parametric instability of functionally graded (FG) rectangular plates in thermal environments is investigated via multi-modal energy approach. Nonlinear higher-order shear deformation theory is used and the nonlinear response to in-plane static and harmonic excitation in the frequency neighbourhood of twice the fundamental frequency is investigated. The boundary conditions are assumed to be simply supported movable. The plate displacements and rotations are expanded in terms of double series trigonometric functions and Lagrange equations are used to reduce the energy functional to a system of infinite nonlinear ordinary differential equations with time varying coefficients, and quadratic and cubic nonlinearities. In order to obtain the complete dynamic scenario, numerical analyses are carried out by means of pseudo arc length continuation and collocation technique to obtain frequency-amplitude and force-amplitude relations in the presence of temperature variation in the thickness direction. The effect of volume fraction exponent as well as temperature variation on the on-set of instability for both static and periodic in-plane excitation are fully discussed and the post-critical nonlinear responses are obtained.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.434
Threshold uncertainty score0.315

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.006
GPT teacher head0.184
Teacher spread0.178 · 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 designObservational
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

Citations1
Published2012
Admission routes1
Has abstractyes

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