MétaCan
Menu
Back to cohort
Record W2418275252 · doi:10.1177/1045389x16649701

Modelling and simulation of surface-bonded piezoelectric actuators with bending effects

2016· article· en· W2418275252 on OpenAlexafffund
Huangchao Yu, Xiaodong Wang

Bibliographic record

VenueJournal of Intelligent Material Systems and Structures · 2016
Typearticle
Languageen
FieldEngineering
TopicComposite Structure Analysis and Optimization
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaChina Scholarship Council
KeywordsActuatorPiezoelectricityBendingMaterials scienceStructural engineeringChebyshev polynomialsSurface (topology)Shear (geology)Composite materialEngineeringGeometryMathematicsMathematical analysis

Abstract

fetched live from OpenAlex

In the modelling of thin-sheet piezoelectric actuators the effect of bending of the actuator itself is usually ignored. The current paper presents a model of a surface bonded piezoelectric actuator subjected to electric loading, which contains both the axial and bending deformations. The static electromechanical response of the actuator is studied under different mechanical and geometrical conditions to evaluate the effect of bending. An imperfectly bonded interface is proposed to simulate debonding and to study its effect on the actuation process. The problem is formulated as integral equations in terms of the interfacial shear and normal stresses, which are solved by using Chebyshev polynomials. Based on the solution, the effect of bending of the actuator upon load transfer is analysed. Illustrative examples are presented to show the effect of the material property, the geometry and the interfacial debonding on the response of the integrated structure.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.201
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

Citations19
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Intelligent Material Systems and StructuresSame topicComposite Structure Analysis and OptimizationFrench-language works237,207