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Record W1997359267 · doi:10.1115/power2013-98224

Investigation of Fluid Dynamic Properties of Liquid Field’s Metal

2013· article· en· W1997359267 on OpenAlexafffund
Adam Lipchitz, Theophile Imbert, Glenn Harvel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldDecision Sciences
TopicScientific Measurement and Uncertainty Evaluation
Canadian institutionsOntario Tech University
FundersSolar Energy Technologies OfficeNatural Sciences and Engineering Research Council of CanadaUniversity of Ontario Institute of Technology
KeywordsMaterials scienceEutectic systemViscosityBismuthLiquid metalViscometerThermodynamicsTinMetalTernary operationAnalytical Chemistry (journal)MetallurgyAlloyChemistryComposite material

Abstract

fetched live from OpenAlex

The density and viscosity Field’s metal is measured in this work and compared to traditional liquid metal coolants such as sodium and lead-bismuth eutectic. Field’s metal is a eutectic of the ternary In-Bi-Sn system. The alloy is by weight percent is 51% indium, 32.5% bismuth and 16.5% tin and possesses a melting temperature of 333 K. This work experimentally measures the density and viscosity of Field’s metal for numerical modeling and thermal hydraulic applications. The density of Field’s metal is measured using a pycnometer. The density is determined for both its solid and liquid states. In its liquid state Field’s metal is found to have a linear dependence with respect to increasing temperature. The viscosity of Field’s metal is measured using a rotational viscometer. The viscosity is measured is to be 27 mPa-s at 353 K, however further investigation is required to determine a trend at higher temperatures.

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)0.000
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 score0.001
Threshold uncertainty score0.003

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0010.000

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 head0.277
GPT teacher head0.358
Teacher spread0.081 · 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

Citations9
Published2013
Admission routes2
Has abstractyes

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