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Record W2008419093 · doi:10.1115/ht2009-88340

Performance Improvement in Pulsating Heat Pipes Using a Self-Rewetting Fluid

2009· article· en· W2008419093 on OpenAlexaff
Koji Fumoto, Masahiro Kawaji

Bibliographic record

VenueVolume 3: Combustion, Fire and Reacting Flow; Heat Transfer in Multiphase Systems; Heat Transfer in Transport Phenomena in Manufacturing and Materials Processing; Heat and Mass Transfer in Biotechnology; Low Temperature Heat Transfer; Environmental Heat Transfer; Heat Transfer Education; Visualization of Heat Transfer · 2009
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Boiling Studies
Canadian institutionsUniversity of Toronto
FundersMinistry of Education, Science and Technology
KeywordsHeat pipeSurface tensionMaterials scienceWorking fluidBoilingHeat transferTube (container)ThermodynamicsHeat transfer enhancementComposite materialMechanicsHeat transfer coefficient

Abstract

fetched live from OpenAlex

New experimental results have been obtained on the enhancement of heat transport by a pulsating heat pipe (PHP) using a self-rewetting fluid. Self-rewetting fluids have a property that the surface tension increases with temperature unlike other common liquids. The increasing surface tension at a higher temperature could cause the liquid to be drawn towards a heated surface if a dry spot appears, and improving boiling heat transfer. In the present experiments, 1-butanol was added to water at a concentration of less than 1 wt% to make the self-rewetting fluid. A pulsating heat pipe made from an extruded multi-port tube was partially filled with the butanol-water mixture and tested for its heat transport capability at different input power levels. The experiments showed that the maximum heat transport capability was enhanced by a factor of four when the maximum heater temperature was limited to 120 °C. Thus, the use of a self-rewetting fluid in a PHP has been shown to be highly effective in improving the heat transport capability of pulsating heat pipes.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesMeta-epidemiology (narrow), Research integrity
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 score0.028
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0040.005
Meta-epidemiology (broad)0.0060.001
Bibliometrics0.0040.003
Science and technology studies0.0010.001
Scholarly communication0.0010.003
Open science0.0010.000
Research integrity0.0040.004
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 head0.007
GPT teacher head0.221
Teacher spread0.214 · 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; both teacher heads agree on what is shown here.

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

Citations8
Published2009
Admission routes1
Has abstractyes

Explore more

Same venueVolume 3: Combustion, Fire and Reacting Flow; Heat Transfer in Multiphase Systems; Heat Transfer in Transport Phenomena in Manufacturing and Materials Processing; Heat and Mass Transfer in Biotechnology; Low Temperature Heat Transfer; Environmental Heat Transfer; Heat Transfer Education; Visualization of Heat TransferSame topicHeat Transfer and Boiling StudiesFrench-language works237,207