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DIMENSIONLESS CORRELATIONS FOR CONVECTIVE HEAT TRANSFER IN CANNED PARTICULATE FLUIDS UNDER AXIAL ROTATION PROCESSING

2009· article· en· W2144293593 on OpenAlexaff
Mritunjay Dwivedi, Hosahalli S. Ramaswamy

Bibliographic record

VenueJournal of Food Process Engineering · 2009
Typearticle
Languageen
FieldEngineering
TopicGranular flow and fluidized beds
Canadian institutionsMcGill University
Fundersnot available
KeywordsDimensionless quantityNatural convectionMechanicsThermodynamicsHeat transferConvectionHeat transfer coefficientConvective heat transferCombined forced and natural convectionChemistryForced convectionRADIUSPhysics

Abstract

fetched live from OpenAlex

ABSTRACT Dimensionless correlations for estimating heat transfer coefficients (U and hfp) in canned high viscosity Newtonian liquids (with and without particles) were developed using stepwise multiple nonlinear regressions of statistically significant dimensionless groups using tangent as an estimate and Newton as search method. Data on overall heat transfer coefficient U and fluid‐to‐particle heat transfer coefficients hfpwere obtained for several processing conditions and were analyzed separately for particle and particle‐free conditions. In free axial mode, a newly developed form, combining natural and forced convection, provided higher R2 = 0.93. In the absence of particles in end‐over‐end mode, introducing natural convection term (Gr × Pr), improved R2 from 0.81 to 0.97. Combination of the reel radius, radius of the can and radius of the particles was chosen as characteristics length. PRACTICAL APPLICATIONS Most earlier dimensionless correlations for a canned liquid particulate mixture subjected to free axial mode of agitation are present for either U or hfp individually due to the difficulties in obtaining time–temperature profiles of the liquid and particles simultaneously; however, the time–temperature prediction at the particle center requires appropriate correlations for both U and hfp and cannot be made with only one of these coefficients. Additionally, importance of natural convection in forced convection heat transfer correlations has been demonstrated by developing the U and hfp correlations using the mixed convection approach as the combination of natural and forced convection heat transfer. These developed correlations would help in modeling the time–temperature profiles of a canned particulate mixture and will be helpful in determining the contribution of natural and forced convection heat transfer. These dimensional numbers would give a better understanding of the physical phenomenon and can also be easily used for scale‐up purposes.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.007

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.227
Teacher spread0.217 · 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 source (direct Gemma or distilled Codex), 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

Citations7
Published2009
Admission routes1
Has abstractyes

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