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Record W2099883404 · doi:10.1098/rspa.2009.0543

The transient coupled thermo-piezoelectric response of a functionally graded piezoelectric hollow cylinder to dynamic loadings

2009· article· en· W2099883404 on OpenAlexaff
M. H. Babaei, Zengtao Chen

Bibliographic record

VenueProceedings of the Royal Society A Mathematical Physical and Engineering Sciences · 2009
Typearticle
Languageen
FieldEngineering
TopicThermoelastic and Magnetoelastic Phenomena
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsLaplace transformPiezoelectricityMaterials scienceGalerkin methodTransient responseMechanicsMaterial propertiesThermal conductionFinite element methodTime domainHomogeneity (statistics)Partial differential equationTransient (computer programming)Mathematical analysisComposite materialPhysicsMathematicsThermodynamicsEngineeringComputer science

Abstract

fetched live from OpenAlex

The transient, coupled thermo-piezoelectric response of a functionally graded, radially polarized hollow cylinder under dynamic axisymmetric loadings was investigated in the present paper. To take into account the simultaneous coupling of displacement, temperature and electric fields as well as non-Fourier heat conduction effect, the Chandrasekharaiah theory of generalized thermo-piezoelectricity was employed. Except thermal relaxation time which was taken to be constant, profiles of all other material properties follow a volume-fraction-based rule with different non-homogeneity indices for each property. To solve three governing coupled partial differential equations, the Galerkin finite-element method was used in the Laplace domain. To restore time, a numerical scheme was employed for the Laplace inversion. When the cylinder was exposed to a highly transient thermal loading, effects of the non-homogeneity index and thermal relaxation time on the results were 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)0.000
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.002

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
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 head0.005
GPT teacher head0.190
Teacher spread0.185 · 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

Citations44
Published2009
Admission routes1
Has abstractyes

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