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Record W3200867208 · doi:10.3390/designs5040058

Expanded Microchannel Heat Exchanger: Finite Difference Modeling

2021· article· en· W3200867208 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueDesigns · 2021
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsWestern University
FundersOffice of Naval ResearchUniversity of ColoradoAmerican Society of Heating, Refrigerating and Air-Conditioning EngineersNew York State Energy Research and Development AuthorityM.J. Murdock Charitable Trust
KeywordsHeat transferMechanicsMicrochannelFinite differenceHeat exchangerManifold (fluid mechanics)Inlet manifoldFinite difference methodWork (physics)Flow (mathematics)Materials scienceVolumetric flow rateThermodynamicsMathematicsMechanical engineeringPhysicsEngineeringMathematical analysis

Abstract

fetched live from OpenAlex

A finite difference model of a heat exchanger (HX) considered maldistribution, axial conduction, heat leak, and the edge effect, all of which are needed to model a high effectiveness HX. An HX prototype was developed, and channel height data were obtained using a computerized tomography (CT) scan from previous work along with experimental results. This study used the core geometry data to model results with the finite difference model, and compared the modeled and experimental results to help improve the expanded microchannel HX (EMHX) prototype design. The root mean square (RMS) error was 3.8%. Manifold geometries were not put into the model because the data were not available, so impacts of the manifold were investigated by varying the temperature conditions at the inlet and exit of the core. Previous studies have not considered the influence of heat transfer in the manifold on the HX effectiveness when maldistribution is present. With no flow maldistribution, manifold heat transfer increases overall effectiveness roughly as would be expected by the greater heat transfer area in the manifolds. Manifold heat transfer coupled with flow maldistribution for the prototype, however, causes a decrease in the effectiveness at high flow rate, and an increase in effectiveness at low flow rate.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.936
Threshold uncertainty score0.464

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 head0.051
GPT teacher head0.232
Teacher spread0.181 · 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