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Record W2059980111 · doi:10.1121/1.4779242

Diffusion of ultrasonic waves in porous glass bead sinters

2002· article· en· W2059980111 on OpenAlexaff
J. H. Page, James V. Beck, Russel Holmes, J. S. Bobowski

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2002
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRandom lasers and scattering media
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsDiffusionUltrasonic sensorWavelengthMaterials scienceScatteringOpticsLongitudinal waveReflection (computer programming)PorosityPorous mediumMean free pathBeadAcoustic waveWave propagationPhysicsAcousticsComposite materialThermodynamics

Abstract

fetched live from OpenAlex

Sintered networks of glass beads form an interesting example of a porous medium, analogous to a very porous rock, in which very strong multiple scattering of elastic waves is observed when the ultrasonic wavelength is comparable with the size of the pores. To investigate the diffusive transport of energy by multiply scattered waves, the transmission of the diffuse energy flux through finite slabs of this material has been measured. From these data, the diffusion coefficient D, as well as the absorption time, was determined by fitting the predictions of the diffusion approximation to the experimental time-of-flight profiles. To accurately measure D, the internal reflection of diffuse waves at the sample boundaries was taken into account by extending the method used previously for acoustic waves [J. H. Page et al., Phys. Rev. E 52, 3106 (1995)]. The frequency dependence of the diffusion coefficient was measured over an extended range of frequencies, and compared with estimates of D from ballistic measurements of the scattering mean free path and group velocity. Because of its relatively simple structure, this material may be an ideal system for probing the diffusion of elastic waves, where diffuse waves have mixed character consisting of both longitudinal and transverse polarizations.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score0.206

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 communication0.0000.000
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 head0.008
GPT teacher head0.216
Teacher spread0.208 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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