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Record W4211138532 · doi:10.32920/ryerson.14658030.v1

A quasi-two-dimensional finite element formulation for analysis of active-passive constrained layer beams

2021· preprint· en· W4211138532 on OpenAlexaff
Jean-Jacques R. Boiluea Bekuit

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEngineering
TopicStructural Engineering and Vibration Analysis
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsConstrained-layer dampingBeam (structure)ViscoelasticityTimoshenko beam theoryFinite element methodPiezoelectricityDisplacement fieldConstitutive equationDependency (UML)Newmark-beta methodMathematical analysisPhysicsVibrationStructural engineeringClassical mechanicsMathematicsVibration controlAcousticsEngineering

Abstract

fetched live from OpenAlex

Active-passive damping is getting more popular with designers because it combines the complementary passive and active features in the control of structural vibrations. The classical three-layer structure has a viscoelastic-layer sandwiched between the host beam and a piezoelectric-layer. The more prevalent assumptions for modeling the system are the use of Euler-Bernoulli beam theory for both the host beam and piezoelectric-layer, and Timoshenko beam theory for the viscoelastic-layer. The assumption that transverse displacement is constant through the thickness limits accuracy and applicability of the model. The current formulation expresses the through-the-thickness dependency of the field variables as polynomials while their span dependency across a finite element is cubically interpolated. The versatility of the formulation is demonstrated via static and dynamic studies of examples taken from the literature. A beam treated with active-passive damping is presented and examined. The constitutive relation of the viscoelastic layer is represented using fractional derivatives and the Grünwald approximation. The extended Hamilton's principle is used to derive the system governing equations which are integrated with the Newmark time-integration system.

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 categoriesMeta-epidemiology (narrow)
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 score0.857
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
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 head0.020
GPT teacher head0.273
Teacher spread0.252 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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