MétaCan
Menu
Back to cohort
Record W2615519190

Heat and Mass Transfer Around a Bubble on a Horizontal Surface in a Subcooled Flow

2016· dissertation· en· W2615519190 on OpenAlexfundno aff
Maryam Medghalchi

Bibliographic record

VenueTSpace (University of Toronto) · 2016
Typedissertation
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsnot available
FundersUniversity of Toronto
KeywordsSubcoolingBubbleMechanicsMass transferFlow (mathematics)Heat transferSurface (topology)Materials scienceThermodynamicsPhysicsMathematicsGeometry
DOInot available

Abstract

fetched live from OpenAlex

Early state heat and mass transfer processes around a nucleated bubble in a subcooled flow boiling is studied numerically. The model uses both boiling and condensation processes, in which microlayer evaporation, thermal boundary layer conduction and kinetic theory evaporation and condensation heat and mass transfer mechanisms, are included. In addition, the model includes a microlayer thickness prediction. \nThe model is applied on a two-dimensional and a three-dimensional computational domain at different subcooling temperatures and flow velocities in presence of gravity. The heated surface superheat and the system pressure are kept constant in all simulations. The two phase model, Volume of Fluid (VOF) in ANSYS/FLUENT is used. \nThe results of the study show the importance of each of the heat transfer mechanisms in various stages of the bubble growth. At the early stages of the bubble growth, the microlayer heat transfer is the dominant transfer mechanism, however, as the bubble grows, the evaporation through bubble upper surface becomes significant. Furthermore, results indicate that the isothermal bubble assumption, which is used in prior models, is not valid for the whole life of bubble growth. \nThe new bubble diameter correlation is concluded from theoretical analysis, which is the function of both √t and t with the coefficient of Ja and Pr numbers. The numerical model predicted bubble lift off diameter at p=2.5atm,〖∆T〗_sup=9℃,〖∆T〗_sub=15℃ is 0.36mm that is predicted experimentally 0.39mm at the same operating conditions. By 7% of underestimation of lift off diameter, the numerical model is validated.

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 categoriesMeta-epidemiology (narrow)
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 score0.741
Threshold uncertainty score1.000

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)0.0010.000

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 head0.005
GPT teacher head0.186
Teacher spread0.182 · 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.

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

Citations1
Published2016
Admission routes1
Has abstractyes

Explore more

Same venueTSpace (University of Toronto)Same topicFluid Dynamics and MixingFrench-language works237,207