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Record W2295517049 · doi:10.1109/tuffc.2016.2519348

A New High-Temperature Ultrasonic Transducer for Continuous Inspection

2016· article· en· W2295517049 on OpenAlexafffund
Mohammad Hossein Amini, Anthony N. Sinclair, Thomas W. Coyle

Bibliographic record

VenueIEEE Transactions on Ultrasonics Ferroelectrics and Frequency Control · 2016
Typearticle
Languageen
FieldEngineering
TopicUltrasonics and Acoustic Wave Propagation
Canadian institutionsUniversity of Toronto
FundersNatural Sciences and Engineering Research Council of CanadaMitacs
KeywordsMaterials scienceTransducerUltrasonic sensorCeramicPiezoelectricityAcoustic impedanceComposite materialPMUTAcoustics

Abstract

fetched live from OpenAlex

A novel design of piezoelectric ultrasonic transducer is introduced, suitable for operation at temperatures of up to 700 °C-800 °C. Lithium niobate single crystal is chosen as the piezoelectric element primarily due to the high Curie temperature of 1200 °C. A backing element based on a porous ceramic is designed for which the pore volume fraction and average pore diameter in the ceramic matrix can be controlled in the manufacturing process; this enables the acoustic impedance and attenuation to be selected to match their optimal values as predicted by a one-dimensional transducer model of the entire transducer. Porous zirconia is selected as the ceramic matrix material of the backing element to obtain an ultrasonic signal with center frequency of 2.7-3 MHz, and 3-dB bandwidth of 90%-95% at the targeted operating temperature. Acoustic coupling of the piezocrystal to the backing element and matching layer is investigated using commercially available high-temperature adhesives and brazing alloys. The performance of the transducer as a function of temperature is studied. Stable bonding and clear signals were obtained using an aluminum brazing alloy as the bonding agent.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.005
GPT teacher head0.184
Teacher spread0.179 · 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 designBench or experimental
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

Citations57
Published2016
Admission routes2
Has abstractyes

Explore more

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