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Record W6983471699

Modeling Three-dimensional Flow and Heat Transfer in Variable Surface Tension Two-phase Flows

2013· dissertation· en· W6983471699 on OpenAlexvenueno aff

Bibliographic record

VenueLibrary and Archives Canada (Government of Canada) · 2013
Typedissertation
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAdvanced Electron Microscopy Techniques and Applications
Canadian institutionsnot available
Fundersnot available
KeywordsMarangoni effectMarangoni numberHeat transferSurface tensionMomentum (technical analysis)ConvectionPosition (finance)Flow (mathematics)Volume of fluid methodConvective heat transfer
DOInot available

Abstract

fetched live from OpenAlex

In the present study a parallel three dimensional Volume of Fluid (VOF) method is developed to simulate Marangoni force in immiscible fluids with variable surface tension. Conservation equations are solved based on cell-averaged one-field volume tracking scheme. Evaluating the convective term in the energy equation along the boundary between the fluids highly depends on the position and orientation of the interface; hence, using average cell values simply ignores the interface shape and leads to computational uncertainty. As a remedy to this issue, the original idea behind the volume tracking method is used not only to advect mass and momentum but also energy across cells. To verify the proposed algorithm, results are compared against theoretically predicted thermocapillary migration velocity of a droplet at the limit of zero Marangoni number. However, at relatively high Marangoni numbers, thermal boundary layers are very thin and challenging to resolve. To demonstrate the capabilities of the heat transfer module, simulations of a Fluorinert droplet moving in silicon oil under applied temperature gradient in microgravity are compared against the available experimental results and the migration velocity of the droplet are reported.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.240
Threshold uncertainty score0.951

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 head0.003
GPT teacher head0.202
Teacher spread0.199 · 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 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

Citations0
Published2013
Admission routes1
Has abstractyes

Explore more

Same venueLibrary and Archives Canada (Government of Canada)Same topicAdvanced Electron Microscopy Techniques and ApplicationsFrench-language works237,207