MétaCan
Menu
Back to cohort
Record W4401718416 · doi:10.1063/5.0207969

Air-coupled ultrasound using broadband shock waves from piezoelectric spark igniters

2024· article· en· W4401718416 on OpenAlex

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.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueApplied Physics Letters · 2024
Typearticle
Languageen
FieldEngineering
TopicFlow Measurement and Analysis
Canadian institutionsUniversity of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaMitacsGovernment of Alberta
KeywordsMaterials scienceShock waveBroadbandSPARK (programming language)Electric sparkAcousticsMicrosecondUltrasonic sensorBandwidth (computing)PiezoelectricityShock (circulatory)OpticsPhysicsEngineering

Abstract

fetched live from OpenAlex

We used an optomechanical sensor to study the ultrasound generated by manually operated piezoelectric spark igniters. These low-energy sparks produce short-duration acoustic shock-wave pulses, with sub-microsecond rise times and frequency content extending well beyond 2 MHz in air. The same source–receiver combination was then used to demonstrate broadband characterization of solid (polymer and glass) plates in a simple setup, where single spark events yielded high signal-to-noise ratio data without the need for critical alignment. This setup also enabled us to estimate pressure excursions approaching 105 Pa at millimeter-scale distances from the spark. The results are in large part made possible by the small size, wide bandwidth, and high sensitivity of the optomechanical sensor and might be of interest for air-coupled ultrasound applications in nondestructive testing.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.642
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.013
GPT teacher head0.197
Teacher spread0.184 · 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