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Record W4414422420 · doi:10.1121/10.0039388

High-frequency dynamic acoustic field manipulation method and its application to flaw evaluation and imaging

2025· article· en· W4414422420 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.

Bibliographic record

VenueThe Journal of the Acoustical Society of America · 2025
Typearticle
Languageen
FieldEngineering
TopicNon-Destructive Testing Techniques
Canadian institutionsUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
FundersNational Natural Science Foundation of China
KeywordsField (mathematics)Ultrasonic sensorOrientation (vector space)Rotation (mathematics)Ultrasonic testing

Abstract

fetched live from OpenAlex

Existing approaches for acoustic field manipulation using acoustic lenses mainly focuses more on low-frequency, particularly audible range, and static fields with limited applicability to ultrasonic regimes. This paper proposes a megahertz-range rotational acoustic field manipulation method based on an acoustic lens and investigates its application in flaw evaluation and imaging. Theoretical analysis of dynamic acoustic field propagation was conducted at frequencies up to the megahertz range, leading to the formulation of a motion-modulated transmission model to describe field regulation. Additionally, a composite flaw evaluation method was introduced based on directional rotation of the dynamic field. Simulation and experimental results demonstrate that this method offers superior performance in directly identifying the orientation and size of flaws with a maximum angle error of only 0.3%. Compared to traditional ultrasonic imaging, this method provides 15% and 18% improvements in accuracy of angle and size, respectively, and presents an efficient guide for dynamic ultrasonic field manipulation and directional field application.

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)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.845
Threshold uncertainty score0.256

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.009
GPT teacher head0.302
Teacher spread0.292 · 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