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Record W2167099329 · doi:10.1109/icmens.2004.1509027

Analytical Modeling and Quantitative Analysis of Scratch Drive Actuator

2006· article· en· W2167099329 on OpenAlexaff
Jean W. Zu, Qiuzhen Qu, Gong Cheng

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsScratchActuatorVoltageComputer scienceState (computer science)Automotive engineeringMechanical engineeringElectrical engineeringEngineeringArtificial intelligenceAlgorithm

Abstract

fetched live from OpenAlex

A new analytical model of Scratch Drive Actuator (SDA) is proposed, which considers its deforming states and geometry characteristics. This model contains three kinds of conditions: low driving voltage, critical driving voltage and high driving voltage. The storing strain energy in the SDA is studied under different conditions because the working performance of the SDA mainly depends on it. Analysis results demonstrate that it is necessary to choose appropriate design parameters of the SDA so that the SDA works near the critical state. Finally, discussions and suggestions for the design of SDA are presented in this paper.

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 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 score0.149
Threshold uncertainty score0.237

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)0.0000.000

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 head0.015
GPT teacher head0.262
Teacher spread0.247 · 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.

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

Citations6
Published2006
Admission routes1
Has abstractyes

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