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Record W2134214742 · doi:10.1109/icmens.2004.1508993

Modeling and Experiments of Input-Output Displacement Relations for a Piezoelectric Nanopositioner

2006· article· en· W2134214742 on OpenAlexaff
Lin Wu, Qiao Sun

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced machining processes and optimization
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDisplacement (psychology)ActuatorControl theory (sociology)PiezoelectricityLock (firearm)Range (aeronautics)Mechanism (biology)Process (computing)Computer scienceStructural engineeringEngineeringAcousticsPhysicsControl (management)

Abstract

fetched live from OpenAlex

Existing commercially available long range piezoelectric actuators have limited load carrying capacity due to the fact that frictions are used as the load bearing mechanism. In order to improve the load carry capacity for long range piezoelectric actuators with nanometer resolutions, a novel design that employs the self-lock concept has been reported. In this paper, we study the input-output displacement relations for this new design. In particular, we investigate the losses of the actuator displacement due to elastic deformations when a large force is applied. For a given load, a minimum value exists for the stroke command to ensure a non-zero output displacement. A positioning strategy was proposed to achieve a nanometer scale positioning process in a long distance. Experimental results were also given to support the analysis.

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)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0010.000
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 head0.008
GPT teacher head0.232
Teacher spread0.224 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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