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Record W2114816975 · doi:10.1139/l05-014

Measurements of void fraction and bubble properties on a stepped chute using a fiber-optic probe

2005· article· en· W2114816975 on OpenAlexvenueno aff
Mohamed K. Elkamash, Mark Loewen, N. Rajaratnam

Bibliographic record

VenueCanadian Journal of Civil Engineering · 2005
Typearticle
Languageen
FieldEngineering
TopicHydraulic flow and structures
Canadian institutionsnot available
Fundersnot available
KeywordsBubblePorosityMechanicsLocal VoidMaterials scienceVoid (composites)Flow measurementVolumetric flow rateTwo-phase flowOpticsAcousticsFlow (mathematics)Composite materialPhysics

Abstract

fetched live from OpenAlex

This paper presents results from an experimental laboratory study conducted to investigate the use of a fiber-optic probe for measuring void fraction, bubble sizes, and bubble velocities in the highly aerated flow generated over a stepped chute. The accuracy of the measurements was verified by comparing the discharge measured by using a magnetic flow meter with the integrated discharge computed from the time averaged void fraction and bubble velocity measurements. At a sample rate of 20 kHz the average errors in the void fraction, bubble velocity, and bubble size were estimated to be 1%, 5%, and 6%, respectively. Increasing the data sample rate reduces the errors in the bubble size and velocity. It was concluded that this fiber-optic probe is well suited for making measurements of the void fraction, bubble sizes, and bubble velocities in a unidirectional two-phase flow.Key words: stepped chute, jet flow, air entrainment, fiber-optic probe, air bubble.

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 studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
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 head0.020
GPT teacher head0.188
Teacher spread0.169 · 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

Citations6
Published2005
Admission routes1
Has abstractyes

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