MétaCan
Menu
Back to cohort
Record W133965865

Modeling and analysis of a resonant sensor actuated by a bent beam thermal actuator

2006· article· en· W133965865 on OpenAlex
Pezhman A. Hassanpour, William L. Cleghorn, Ebrahim Esmailzadeh, James K. Mills

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venueinternational conference on Modelling and simulation · 2006
Typearticle
Languageen
FieldEngineering
TopicAdvanced MEMS and NEMS Technologies
Canadian institutionsOntario Tech UniversityUniversity of Toronto
Fundersnot available
KeywordsBeam (structure)ActuatorVibrationResonatorNatural frequencyThermalStiffnessMicroelectromechanical systemsDisplacement (psychology)MechanicsMaterials scienceProof massPhysicsAcousticsOpticsOptoelectronicsEngineeringThermodynamicsElectrical engineering
DOInot available

Abstract

fetched live from OpenAlex

In this paper, a micromechanical system (MEMS) is modeled analytically. The system consists of three parts: a double-ended tuning fork (DETF), a bent beam thermal actuator, and a suspending mass. The suspending mass transmits the force from the thermal actuator to the DETF and prevents thermal stress to be produced in the DETF by precluding heat transfer to it. The thermal force-displacement equations, including the effect of axial stiffness of the resonator, are derived. The natural frequency of the vibration of DETF is a function of applied force to it. The DETF is modeled as two parallel beams, each carrying a concentrated mass in its interval. The characteristic equation of the vibration, which gives the exact values of the natural frequencies of the beam, is derived using method of separation of variables. The effects of the temperature rise as well as the system geometry on the natural frequency of the beam are discussed in detail.

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.

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 score0.327
Threshold uncertainty score0.350

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 head0.029
GPT teacher head0.265
Teacher spread0.235 · 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