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Record W2011797992 · doi:10.1002/cjce.5450780607

Heat and mass transfer in granular potash fertilizer with a surface dissolution reaction

2000· article· en· W2011797992 on OpenAlex
Shi‐Wen Pen, Robert W. Besant, Graeme Strathdee

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.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2000
Typearticle
Languageen
FieldEngineering
TopicAdsorption and Cooling Systems
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsMass transferThermodynamicsRelative humidityHeat transferDissolutionParticle (ecology)PotashMoistureHumidityElectrolyteChemistryMaterials scienceMechanicsComposite materialMetallurgyPotassiumPhysical chemistryElectrode

Abstract

fetched live from OpenAlex

Abstract Potash is a widely used granular fertilizer and when exposed to high humidities it readily adsorbs water vapour forming a liquid electrolyte solution on each particle. Heat and mass transfer due to air flow through granular potash beds is studied experimentally and numerically. A one dimensional experimental setup is used to measure the temperature and air humidity response and mass gain of a potash bed subjected to a change in air flow. A porous media mathematical model is developed to predict the transient temperature and moisture content distributions. The processes are modelled as nonequilibrium heat and mass transfers between the porous solid and air flow gaseous phases. The state of the surface electrolyte solution is modelled by the thermodynamics of electrolyte solutions. Experimental and numerical results show non‐equilibrium internal moisture and heat transfer processes exist with significant differences in the pore air and particle temperature and surface relative humidity.

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 score0.319
Threshold uncertainty score0.279

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 head0.005
GPT teacher head0.159
Teacher spread0.154 · 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