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Record W2261656746 · doi:10.1002/9781118534892.ch3

Drying Processes and Systems

2015· other· en· W2261656746 on OpenAlexaff
İbrahim Dinçer, Calin Zamfirescu

Bibliographic record

Venuenot available
Typeother
Languageen
FieldEngineering
TopicHeat Transfer Mechanisms
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsTrayProcess engineeringFluidized bedEnvironmental scienceWaste managementMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

This chapter discusses the main types of drying equipment and systems, which are classified under various criteria related to drying materials, operational and technical aspects, efficiency and effectiveness, and so on. It describes batch tray dryers, batch through-circulation dryers, continuous tunnel dryers, rotary dryers, agitated dryers, direct-heat vibrating-conveyor dryers, gravity dryers, dispersion dryers, fluidized bed dryers, drum dryers, and solar drying systems. The details on their applications for various drying materials are explained and illustrated. The most common drying systems namely, natural drying, forced drying, spray drying, freeze-drying, and vacuum drying, are discussed and evaluated in detail. The specific equations for system modeling in natural and forced convection drying processes are briefly introduced and discussed. Some illustrative examples are presented to show how to make respective drying calculations.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.011
Threshold uncertainty score0.466

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 head0.018
GPT teacher head0.208
Teacher spread0.190 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2015
Admission routes1
Has abstractyes

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