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Record W2732267396 · doi:10.21595/mme.2017.18228

Resonance vibration of an optical fiber micro-cantilever using electro-thermal actuation

2017· article· en· W2732267396 on OpenAlexaff
Mojtaba Komeili, Aydin Aghajanzadeh Ahrabi, Carlo Menon

Bibliographic record

VenueMathematical Models in Engineering · 2017
Typearticle
Languageen
FieldEngineering
TopicAdvanced Fiber Optic Sensors
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsCantileverVibrationBoundary value problemAcousticsNatural frequencyResonance (particle physics)Optical fiberFinite element methodHarmonicFiberMaterials scienceFrequency responseOpticsPhysicsStructural engineeringEngineeringMathematical analysisMathematics

Abstract

fetched live from OpenAlex

The resonance excitation of an optical fiber actuated by a conductive wire is studied in this paper. A novel approach based on exciting the micro-cantilever fiber at a location close to its base is proposed for this purpose. Analytical modeling is conducted on the mechanical models of this system in order to predict its behavior. The continuous Euler-Bernoulli beam equation with the effect of surrounding fluid medium is formulated as a boundary value problem. The natural frequencies of the system and its harmonic response are expanded analytically, and results are verified using Finite Element analysis. The obtained analytical solutions are used to draw conclusions on the response of the system and suggestions to optimize its performance are presented. In order to verify the idea in practice, an experimental setup that can closely resemble the system under consideration is made in the laboratory and its response to a periodic input with different frequencies are recorded. Comparison between the results of analytical formulation and experimental observations highlights the effectiveness of suggested technique in resonance vibration of optical fibers.

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 score0.172
Threshold uncertainty score0.865

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 communication0.0000.001
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 head0.022
GPT teacher head0.249
Teacher spread0.227 · 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

Citations4
Published2017
Admission routes1
Has abstractyes

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