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Record W3133706324 · doi:10.11159/jffhmt.2021.018

Influence of Plate Geometry on Thermohydraulic Performance of Fixed-Bed Regenerators

2021· article· en· W3133706324 on OpenAlexafffundvenue
Easwaran N. Krishnan, Hadi Ramin, A. Gurubalan, Carey J. Simonson

Bibliographic record

VenueJournal of Fluid Flow Heat and Mass Transfer · 2021
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Optimization
Canadian institutionsUniversity of Saskatchewan
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Saskatchewan
KeywordsGeometryMaterials scienceMechanicsMathematicsPhysics

Abstract

fetched live from OpenAlex

is a type of air-to-air energy exchanger used to reduce the energy consumption in HVAC systems. Employing corrugated plates improves the heat transfer performance of FBRs. In this study, the thermohydraulic performance of an FBR with corrugated plates is compared with that of an FBR with parallel plates. The sensible effectiveness of corrugated plate FBR is experimentally evaluated in a smallscale test facility. A validated numerical model is used to predict the performance of the parallel plate FBR. The average heat transfer coefficient of corrugated FBR is determined from the measured data and Kays and London regenerator correlation. The heat transfer coefficient and effectiveness of corrugated plate FBR are 150% and 37% higher than those of parallel pate FBR at a Reynolds number of 1450. Similarly, the friction factor of corrugated FBR is also increased nearly six times that of parallel plate FBR. Results from the present study can be used to design FBRs and evaluate their effectiveness for a range of Reynolds numbers from 500 to 1450.

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 score0.428
Threshold uncertainty score0.461

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 head0.006
GPT teacher head0.190
Teacher spread0.184 · 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

Citations1
Published2021
Admission routes3
Has abstractyes

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