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Record W1560693368 · doi:10.1063/1.1307887

High resolution measurements in liquid metal by focused ultrasonic wave

2000· article· en· W1560693368 on OpenAlexaff
Ikuo IHARA

Bibliographic record

VenueAIP conference proceedings · 2000
Typearticle
Languageen
FieldEngineering
TopicNon-Destructive Testing Techniques
Canadian institutionsNational Research Council Canada
Fundersnot available
KeywordsMaterials scienceUltrasonic sensorZincRodPhase (matter)SIGNAL (programming language)AcousticsAcoustic holographyOpticsHolographyMetallurgyPhysics

Abstract

fetched live from OpenAlex

High spatial resolution measurements in molten zinc at temperatures more than 600 °C are performed using a focused ultrasonic pulse-echo technique with clad metallic buffer rods. The focused ultrasonic waves are generated by a spherical acoustic lens which is fabricated at the end of the buffer rod. In order to evaluate its focussing ability, several experiments are carried out in molten zinc at 10 MHz. First, high resolution ultrasonic imaging is performed by raster scanning the sample in the focusing plane. The signal-to-noise ratio of the reflected signals from the sample surface at the focus is better than 35 dB which leads to very good ultrasonic images obtained from the amplitude or phase variation of the reflected signal. Second, the detection of a thin stainless wire with a diameter of 380 μm is carried out at 650 °C in molten zinc. It is found that not only the wire but also small inclusions existing in molten zinc may be detected. Third, in order to perform quantitative evaluation, V(z) curve measurements are performed. Both the leaky surface wave velocity of SiC immersed in molten zinc and the longitudinal velocity of molten zinc at 650 °C are successfully and simultaneously determined from the V(z) curve. Based on these results, the potential ability of this technique for the quantitative evaluation of the cleanliness in molten metals will be discussed.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.035
GPT teacher head0.233
Teacher spread0.197 · 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 designBench or experimental
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

Citations3
Published2000
Admission routes1
Has abstractyes

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