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Record W1997668454 · doi:10.1115/1.2241974

Transient Response of Two-Phase Heat Exchanger With Varying Convection Coefficients

2006· article· en· W1997668454 on OpenAlexafffund
G.F. Naterer, Chun Ho Lam

Bibliographic record

VenueJournal of Heat Transfer · 2006
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsHoneywell (Canada)Ontario Tech University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMechanicsHeat exchangerConvectionThermodynamicsLaplace transformPlate heat exchangerMaterials scienceMathematicsPhysicsMathematical analysis

Abstract

fetched live from OpenAlex

Transient changes of fluid and wall temperatures in a two-phase heat exchanger are investigated in this article, particularly with respect to spatial and temporal effects of varying convection coefficients. The coupled energy equations for both sides of the heat exchanger are solved directly with an integral method. Varying convection coefficients are related to changes of vapor fraction between the inlet and outlet of the heat exchanger. Unlike past numerical studies encountering difficulties with instability, stiffness, and lack of convergence, the current integral formulation provides a reliable alternative and efficient procedure for transient response within the heat exchanger. Furthermore, complex inversion from a transformed domain is not needed, in contrast to conventional methods with Laplace transforms. In this article, past integral methods are extended to cases with varying convection coefficients, arising from changes of phase fraction on the two-phase side of the heat exchanger, as well a multiple step-changes of temperature. The predicted results show close agreement with past data, including numerical simulations with a dynamic simulator.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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)0.0010.000

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 head0.011
GPT teacher head0.238
Teacher spread0.227 · 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 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

Citations15
Published2006
Admission routes2
Has abstractyes

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