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Record W2051282576 · doi:10.1520/gtj101689

New Methodology for Source Characterization in Pulse Velocity Testing

2009· article· en· W2051282576 on OpenAlexaff
Fernando Tallavó, Giovanni Cascante, Mahesh D. Pandey

Bibliographic record

VenueGeotechnical Testing Journal · 2009
Typearticle
Languageen
FieldEngineering
TopicUltrasonics and Acoustic Wave Propagation
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsWaveformAcousticsUltrasonic sensorTransmitterMeasure (data warehouse)Pulse (music)Transient (computer programming)Wave propagationTransducerCharacterization (materials science)Fourier transformFinite element methodEngineeringPhysicsOpticsComputer scienceStructural engineeringTelecommunications

Abstract

fetched live from OpenAlex

Abstract The pulse velocity test (PVT) is an ASTM standard for the measurement of compressional wave velocities in geomaterials. The PVT is based only on the first arrival of the wave. Full-waveform analysis can be used to measure the variation in geomaterial properties with frequency but requires the dynamic characteristics of the transducers. This paper presents a new methodology for the dynamic characterization of ultrasonic transmitters based on experimental and numerical results. Different types of excitation pulses (input signals) are used, and their theoretical Fourier spectra are computed. The methodology is demonstrated using a piezoelectric accelerometer to measure the frequency response function of an ultrasonic transmitter (UT) (50 kHz). The complex exponential method is used to extract the dynamic properties of the transmitter from transient time signals. Experimental results show that this methodology can be used for the dynamic characterization of ultrasonic transmitters. Results from finite element numerical simulations of wave propagation agree with laboratory results.

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Methods · Consensus signal: Methods
Teacher disagreement score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0000.001
Scholarly communication0.0010.002
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.070
GPT teacher head0.278
Teacher spread0.207 · 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 designTheoretical or conceptual
Domainnot available
GenreMethods

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

Citations20
Published2009
Admission routes1
Has abstractyes

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Same venueGeotechnical Testing JournalSame topicUltrasonics and Acoustic Wave PropagationFrench-language works237,207