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Record W3216215465 · doi:10.32920/ryerson.14662458.v1

A Finite Element Formulation Of Active Constrained-Layer Functionally Graded Beam

2021· preprint· en· W3216215465 on OpenAlexaff
Ry Long

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicComposite Structure Analysis and Optimization
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsConstrained-layer dampingBeam (structure)ViscoelasticityFinite element methodTimoshenko beam theoryNewmark-beta methodMaterials scienceCantileverEquations of motionVibrationStructural engineeringHamilton's principleLayer (electronics)Functionally graded materialVibration controlMathematical analysisMathematicsComposite materialPhysicsClassical mechanicsEngineeringAcoustics

Abstract

fetched live from OpenAlex

Active constrained-layer damping (ACLD) treatment is the combination of passive and active features in the control of structural vibrations. A three-layer structure that consists of a functionally graded (FG) host beam, with a bonded viscoelastic layer and a constraining piezoelectric fiber-reinforce composite (PFRC) laminate is modeled and analyzed. The assumptions for modeling the system are the application of Timoshenko beam theory for the host beam and PFRC laminate, and a higher-order beam theory for the viscoelastic layer. The formulation is assumed to have field variables that are expressed as polynomials through the thickness of the structure and linear interpolation across the span. The extended Hamilton's principle is utilized to determine the system equations of motion, which are then solved using the Newmark time-integration scheme. Many support conditions such as fully- and partial-clamped cantilevered, partially clamped-clamped and simply-supported are analyzed. The effects of ply angle orientaion, as well as FG properties, are also carefully examined.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.853
Threshold uncertainty score1.000

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)0.0010.000

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 head0.011
GPT teacher head0.219
Teacher spread0.208 · 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.

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

Citations1
Published2021
Admission routes1
Has abstractyes

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