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INVESTIGATION OF THERMOSYPHON PERFORMANCE WITH CHANGING ADIABATIC SECTION GEOMETRY

2014· article· en· W2634336633 on OpenAlexaff
Kate Smith, Samuel Siedel, A.J. Robinson, Roger Kempers

Bibliographic record

VenueHeat Pipe Science and Technology An International Journal · 2014
Typearticle
Languageen
FieldEngineering
TopicAdvanced Theoretical and Applied Studies in Material Sciences and Geometry
Canadian institutionsYork UniversityMcMaster UniversityTrinity College
Fundersnot available
KeywordsThermosiphonAdiabatic processCondenser (optics)Heat transferMechanicsEvaporatorWork (physics)Materials scienceHeat pipeThermalRange (aeronautics)ThermodynamicsMechanical engineeringHeat exchangerEngineeringPhysicsOpticsComposite material

Abstract

fetched live from OpenAlex

In certain applications geometric constraints may make it impractical to use a straight thermosyphon. This paper aims to characterize the performance of a counter-flow thermosyphon with varying bend angles in the adiabatic section and a range of fluid loadings. The results of this study demonstrate that adequate levels of heat transfer can be achieved with bends in the adiabatic section connecting the evaporator and condenser sections. In general the effects of bend angle and fluid loading had relatively little effect on total thermal resistance. Finally, the failure limit of each thermosyphon was characterized. It was clear from the results obtained that further work is necessary to expand the range of testing parameters to fully understand their influence on the performance of the thermosyphon.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.004
GPT teacher head0.206
Teacher spread0.202 · 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 source (direct Gemma or distilled Codex), 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
Published2014
Admission routes1
Has abstractyes

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