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Record W4402438596 · doi:10.11159/htff24.179

Flow Boiling Characteristics in Expanding Type Structured Heat Sinks for Different Roles of Gravitational Force

2024· article· en· W4402438596 on OpenAlexvenueno aff
Burak Markal, Alperen Evcimeny

Bibliographic record

VenueProceedings of the World Congress on Mechanical, Chemical, and Material Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Boiling Studies
Canadian institutionsnot available
FundersTürkiye Bilimsel ve Teknolojik Araştırma Kurumu
KeywordsBoilingHeat sinkMechanicsGravitational forceFlow (mathematics)GravitationType (biology)Flow boilingComputer scienceMechanical engineeringNucleate boilingPhysicsHeat transferThermodynamicsClassical mechanicsEngineeringGeologyHeat flux

Abstract

fetched live from OpenAlex

The orientation of the devices that must be cooled can change depending on the application requirements.Orientation-based variations can influence the physical mechanism regarding the coolers.Therefore, here, saturated flow boiling in the structured (expanding micro pin-finned with staggered array) micro heat sink is investigated under different angles.Positive and negative orientation of the heat sink have influence on the possible contribution of the gravitational effects.Experimental range includes three angular positions (+30°, 0°, -30°), two mass velocities (G=105 and 210 kg m -2 s -1 ) and a large heat flux interval (194 -366 kW m -2 ).Inlet and ambient temperatures are constant at approximately Ti = 73°C and Ta = 24°C, respectively.It is concluded that optimum thermal performance is got for the horizontal orientation (0°) for both the mass flux values.The wetting process as well as balance of the gravitational force (related to liquid flow) and buoyancy force (related to the vapor flow) plays a key role on the thermal performance.Both the relevant forces are related to inclination angle.The pressure drop at the condition of ϕ = 0° is relatively higher than those of the others (ϕ = +30° and -30°).

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 score0.070
Threshold uncertainty score0.637

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 head0.007
GPT teacher head0.221
Teacher spread0.213 · 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
Published2024
Admission routes1
Has abstractyes

Explore more

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