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Record W2003200838 · doi:10.1002/cjce.21681

Vortex motion‐based particle swarm optimisation for energy consumption of alumina evaporation

2012· article· en· W2003200838 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.

venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2012
Typearticle
Languageen
FieldComputer Science
TopicMetaheuristic Optimization Algorithms Research
Canadian institutionsnot available
FundersNational Science Fund for Distinguished Young ScholarsNational Natural Science Foundation of China
KeywordsSodium aluminateEvaporationParticle swarm optimizationProcess engineeringProcess (computing)Benchmark (surveying)Energy consumptionVortexParticle (ecology)Regenerative heat exchangerMathematical optimizationSteam reformingComputer scienceMaterials scienceEngineeringAlgorithmHeat exchangerMechanical engineeringChemistryMechanicsMathematicsThermodynamicsAluminiumPhysicsComposite material

Abstract

fetched live from OpenAlex

Abstract The aim of the alumina evaporation process is to improve the concentration of sodium aluminate solution by evaporating the excess water contained in the solution. The evaporation is achieved using heat from steam. Since steam consumption is the major operating costs, in this paper, we investigate an operation optimisation problem for the evaporation process to minimise steam consumption subject to a constraint on the particular quality of the final sodium aluminate solution. This paper proposes a new particle swarm optimisation (PSO) algorithm based on vortex motion to solve this optimisation problem. We demonstrate the effectiveness of the PSO algorithm on benchmark functions. We then apply it to a real industrial evaporation process, where the optimal results show that the steam consumption is considerably reduced. © 2012 Canadian Society for Chemical Engineering

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)0.001
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: Methods · Consensus signal: none
Teacher disagreement score0.889
Threshold uncertainty score0.218

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 integrity0.0000.000
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 head0.033
GPT teacher head0.252
Teacher spread0.219 · 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