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Record W2906813 · doi:10.1139/m88-228

NUMERICAL ANALYSIS OF PRESSURE FIELDS OF ACOUSTIC LENS BY METHOD OF PARABOLIC EQUATION

2007· article· en· W2906813 on OpenAlexvenueno aff
Takashi Tsuchiya, Tetsuo Anada, Nobuyuki Endoh, Satoshi Matsumoto

Bibliographic record

VenueCanadian Journal of Microbiology · 2007
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicUnderwater Acoustics Research
Canadian institutionsnot available
Fundersnot available
KeywordsLens (geology)OpticsFocal pointAcousticsUltrasonic sensorFocal lengthParaxial approximationAmplitudeSonarCardinal pointAxial symmetryPhysicsSound pressureUnderwaterComputer simulationMechanicsGeology

Abstract

fetched live from OpenAlex

An acoustic focusing lens is generally used to increase the resolution in applications such as ultrasonic diagnosis, acoustic microscopy and real-time imaging sonar for Autonomous Underwater Vehicle. The aim of this paper is to give a numerical prediction of the behaviours of focusing fields for the biconcave acoustic lens. Based on wave acoustics using axially symmetric parabolic equation with the z-axis as the paraxial direction, focusing property of a progressive ultrasonic wave by biconcave lens is investigated numerically. The focusing amplitude of transmitted ultrasonic wave through the biconcave lens increases with propagation and great oscillations in the amplitude appear in the pre-focal region, takes a maximum gain at the focal point, and then decreases gradually in the post-focal region. Validity of the numerical simulation will be demonstrated by comparing with analysis 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)0.002
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 score0.010
Threshold uncertainty score0.024

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0070.001

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 head0.026
GPT teacher head0.276
Teacher spread0.249 · 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

Citations0
Published2007
Admission routes1
Has abstractyes

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