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Record W2020693580 · doi:10.1109/bmas.2009.5338895

VHDL-AMS behavioural modelling of a CMUT element

2009· article· en· W2020693580 on OpenAlexaff
Samuel Frew, Hadi Najar, Edmond Cretu

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicUltrasonics and Acoustic Wave Propagation
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsVHDL-AMSCapacitive micromachined ultrasonic transducersCapacitive sensingVHDLSoftware portabilityComputer scienceFinite element methodHardware description languageUltrasonic sensorTransducerElectronic engineeringAcousticsEmbedded systemEngineeringField-programmable gate arrayPhysicsProgramming language

Abstract

fetched live from OpenAlex

This paper reports the development, implementation and simulation of a behavioural model written in VHDL-AMS for a capacitive micromachined ultrasonic transducer (CMUT). Unlike previous behavioural models, this model incorporates the non-linear electro-mechanical relation of the CMUT. VHDL-AMS was chosen for the ease with which it can be used to implement these relations, and for its portability between software platforms. To the best of the authors' knowledge, this is the first reported VHDL-AMS model of a CMUT. The simulation results demonstrate that the model can be used to sumulate a number of scenarios, including frequency responses, time responses and effects of DC bias voltage. Results are compared to a finite element method model, and show excellent agreement in resonant frequency and a 16% error in pull-in voltage.

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)0.001
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: none
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0060.001

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 head0.024
GPT teacher head0.200
Teacher spread0.176 · 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

Citations11
Published2009
Admission routes1
Has abstractyes

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