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Heat Dissipation by Streams of Bifurcated Tubes

2021· article· en· W3214713840 on OpenAlexaff
Devaneyan Solomon Nitesh, Murat Aydın, Eda Aydin, António F. Miguel

Bibliographic record

VenueDefect and diffusion forum/Diffusion and defect data, solid state data. Part A, Defect and diffusion forum · 2021
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsDissipationSTREAMSMechanicsFoulingThermal management of electronic devices and systemsFlow (mathematics)Materials sciencePower (physics)ThermodynamicsMechanical engineeringComputer scienceEngineeringPhysicsChemistry

Abstract

fetched live from OpenAlex

There is a need for solutions to provide sufficient cooling from power devices, which produce large amounts of heat. This paper focuses on the influence of design of bifurcated fluid streams to dissipate heat. In this study, a single Y-tubes, a double Y-tubes, and an X-tubes designs are studied numerically under space constraints. For a comprehensive and in-depth performance analysis, both heat dissipation and hydraulic performances are analyzed. The distributions of velocity and temperature in the fluid streams is simulated, also the flow resistances and dissipated heat are calculated. Based on the results obtained, a thermo-hydraulic performance factor is introduced for the designs under study. In addition, the accumulation of undesired substances on the wall surface (fouling) that may influence the heat exchanging capability is studied.

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)0.001
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 score0.614
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.002
Research integrity0.0000.001
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 head0.016
GPT teacher head0.254
Teacher spread0.239 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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