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Record W1996715956 · doi:10.1021/ie0505312

Local Mass Transfer in a Packed Bed:  Experiments and Model

2005· article· en· W1996715956 on OpenAlexafffund
Trong Dang‐Vu, Huu Doan, Ali Lohi

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2005
Typearticle
Languageen
FieldEngineering
TopicHeat and Mass Transfer in Porous Media
Canadian institutionsToronto Metropolitan University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDistributorMass transferPacked bedMass transfer coefficientMechanicsVolumetric flow rateFlow (mathematics)Liquid flowTransfer (computing)ChemistryChromatographyMaterials scienceAnalytical Chemistry (journal)ThermodynamicsPhysics

Abstract

fetched live from OpenAlex

Liquid-to-packing local mass-transfer coefficients (LMTC) were measured in a 0.3 m diameter column with a bed height of 5.5 times the column diameter using the limiting-current technique. Several electrodes were placed at various radial and axial positions (packing heights) in the bed. Measurements were conducted at various liquid flow rates with two different liquid distributor designs: multipoint (MPLD) and single-point (SPLD) distributors. For shallow beds, mass-transfer variation with radial location and liquid flow rate using MPLD was less than that for SPLD. However, for larger bed depths, the local mass-transfer coefficient became less dependent on liquid flow rate with both liquid distributors. A mathematical model for the LMTC in a packed bed was also developed, taking into account the axial and radial positions in the bed. The model predicts the LMTC well with the root-mean-square errors (RMS) of predicted and measured values of 0.07 and 0.08 for the multipoint and single-point liquid distributors, respectively.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.170
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
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 head0.080
GPT teacher head0.314
Teacher spread0.234 · 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 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

Citations7
Published2005
Admission routes2
Has abstractyes

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