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Flow visualization and heat transfer measurements of molten salt natural convection

2025· article· en· W4412419917 on OpenAlexafffund
Noah LeFrançois, Valerie Lamenta, Jovan Nedić, Melanie Tetreault-Friend

Bibliographic record

VenueInternational Journal of Heat and Mass Transfer · 2025
Typearticle
Languageen
FieldEngineering
TopicMetallurgical Processes and Thermodynamics
Canadian institutionsHatch (Canada)McGill University
FundersFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of Canada
KeywordsNatural convectionMaterials scienceHeat transferMolten saltFlow visualizationMechanicsVisualizationConvectionConvective heat transferFlow (mathematics)ThermodynamicsNatural circulationComputer sciencePhysicsMetallurgy

Abstract

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Natural convection is an important mode of heat transfer in the design of molten salt energy technologies. While heat transfer correlations for natural convection in water have been widely studied, there is a lack of equivalent experimental data for molten salts due to material compatibility and instrumentation challenges posed by high-temperature experiments in a corrosive molten salt environment. An experimental investigation of convective heat transfer in a differentially-heated cavity using a binary nitrate salt mixture, NaNO 3 -KNO 3 (60-40 wt % ), is presented with the goal of obtaining empirical heat transfer correlations which can be compared to existing correlations. Particle Image Velocimetry (PIV) measurements are implemented to study changes in the large-scale flow structures with varying Rayleigh number. A triple-paned window design is introduced to address heat losses through the optical window and minimize deviations from ideal differentially-heated cavity boundary conditions. Transitions between Nusselt number scaling regimes are identified through heat transfer measurements and the mean flow field of large-scale circulation cells observed via PIV measurements. Good agreement with existing correlations for water is found in the range of 2 × 1 0 7 < Ra < 2 × 1 0 8 , while the observed heat transfer rates are found to have significantly stronger scaling exponents in the range of 2 × 1 0 8 < Ra < 2 × 1 0 9 .

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 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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.807
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.010
GPT teacher head0.246
Teacher spread0.236 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2025
Admission routes2
Has abstractyes

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