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Record W2132715736 · doi:10.1002/aic.11692

Three‐dimensional CFD model for a flat plate photocatalytic reactor: Degradation of TCE in a serpentine flow field

2008· article· en· W2132715736 on OpenAlexafffund
Asefeh Jarandehei, Alex De Visscher

Bibliographic record

VenueAIChE Journal · 2008
Typearticle
Languageen
FieldEngineering
TopicInnovative Microfluidic and Catalytic Techniques Innovation
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaCanada Research ChairsWestern Canada Research Grid
KeywordsLaminar flowComputational fluid dynamicsLaminar flow reactorMechanicsReynolds numberMixing (physics)PhotocatalysisFlow (mathematics)ChemistryChemical reactorVortexVolumetric flow rateMaterials scienceChemical engineeringThermodynamicsCatalysisOpen-channel flowPhysicsEngineeringTurbulenceOrganic chemistry

Abstract

fetched live from OpenAlex

Abstract Computational fluid dynamics (CFD) simulation was applied to a photocatalytic reactor with surface reaction for trichloroethylene (TCE) oxidation at various pollutant concentrations, and flow rates. First‐order and Langmuir‐Hinshelwood kinetics for TCE removal rate were considered. The results were compared with those from experiments of Demeestere et al. (Appl Catal B Environ. 2004;54:261–274) in a flat plate photocatalytic reactor with serpentine geometry. The flow regime was laminar. Through the CFD simulation, the velocity field and the concentration gradient of TCE in the reactor were studied in detail. At Reynolds numbers around 900, the laminar flow becomes unstable. Under such a condition, when flow passes the 180° sharp turns, due to formation of secondary flow and consequently vortices, there is a lot of cross‐sectional mixing in the reactor. This kind of studies can help us to model the photocatalytic reactor as accurately as possible. © 2008 American Institute of Chemical Engineers AIChE J, 2009

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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.598
Threshold uncertainty score0.511

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 head0.028
GPT teacher head0.249
Teacher spread0.221 · 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

Citations26
Published2008
Admission routes2
Has abstractyes

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