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Record W2037690800 · doi:10.1115/1.1991862

Modeling of Heat Transfer in a Moving Packed Bed: Case of the Preheater in Nickel Carbonyl Process

2005· article· en· W2037690800 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

VenueJournal of Applied Mechanics · 2005
Typearticle
Languageen
FieldEngineering
TopicHeat and Mass Transfer in Porous Media
Canadian institutionsLethbridge CollegeLaurentian University
Fundersnot available
KeywordsAir preheaterPelletHeat transferPelletsMaterials scienceMechanicsPacked bedThermodynamicsNickelThermalChemistryComposite materialMetallurgyPhysicsChromatography

Abstract

fetched live from OpenAlex

Heat transfer in a two-dimensional moving packed bed consisting of pellets surrounded by a gaseous atmosphere is numerically investigated. The governing equations are formulated based on the volume averaging method. A two-equation model, representing the solid and gas phases separately, and a one-equation model, representing both the solid and gas phases, are considered. The models take the form of partial differential equations with a set of boundary conditions, some of which were determined experimentally, and design parameters in addition to the operating conditions. We examine and discuss the parameters in order to reduce temperature differences from pellet to pellet. The calculation results show that by adopting a constant temperature along the preheater outer wall and decreasing the velocity of the pellets in the preheater, the difference in temperature from pellet to pellet is reduced from ∼120°C to ∼55°C, and the thermal efficiency of the preheater is tremendously improved.

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: Empirical
Teacher disagreement score0.135
Threshold uncertainty score0.473

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 head0.010
GPT teacher head0.216
Teacher spread0.206 · 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