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Record W2037131598 · doi:10.1115/1.4002717

Contrapropagating Ultrasonic Flowmeter Using Clad Buffer Rods for High Temperature Measurements

2010· article· en· W2037131598 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

VenueJournal of Dynamic Systems Measurement and Control · 2010
Typearticle
Languageen
FieldEngineering
TopicFlow Measurement and Analysis
Canadian institutionsNational Research Council CanadaMcGill University
Fundersnot available
KeywordsUltrasonic flow meterUltrasonic sensorFlow measurementMaterials scienceRodCalibrationBuffer (optical fiber)Volumetric flow rateTransducerAcousticsFlow (mathematics)Temperature measurementMechanicsElectrical engineeringEngineeringPhysics

Abstract

fetched live from OpenAlex

This work proposes clad buffer rods driven by shear transducers as the main building block of contrapropagating ultrasonic flowmeters for high temperature application. It is demonstrated that the superior signal-to-noise ratio exhibited by clad buffer rods (compared with the reported nonclad counterparts) improves precision in transit time measurements, leading to more accurate flow speed determination. In addition, it is shown that clad buffer rods generate specific ultrasonic signals for temperature calibration of flowmeters, allowing temperature variation while still measuring accurately the flow speed. On the basis of these experimental results, a contrapropagating ultrasonic flowmeter was designed and installed in a heater machine for flow speed measurements of hot oil at temperatures near 130°C. For a temperature variation of 3°C, the difference between upstream and downstream ultrasonic transit times, which is proportional to the flow speed at a given temperature, was measured within 1 ns accuracy.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.946
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.016
GPT teacher head0.213
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