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Record W2955421975 · doi:10.1016/j.ifacol.2019.06.168

Dynamic Optimization Applied for Modelling and Optimal Control of a Packed Bed Reactor for Chemical-Looping Combustion

2019· article· en· W2955421975 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

VenueIFAC-PapersOnLine · 2019
Typearticle
Languageen
FieldEngineering
TopicChemical Looping and Thermochemical Processes
Canadian institutionsUniversity of Waterloo
Fundersnot available
KeywordsChemical looping combustionControllabilityCombustionProcess engineeringProcess (computing)Sensitivity (control systems)Process controlComputer scienceEnvironmental scienceEngineeringChemistry

Abstract

fetched live from OpenAlex

Chemical-looping Combustion (CLC) has recently emerged as a promising technology to curb CO2 emissions. The novelty of CLC resides on its inherent ability of avoid direct contact between the fuel and the air, while producing a highly concentrated CO2 stream. This study presents a dynamic modelling and controllability study that demonstrates the technical feasibility of a fixed bed CLC reactor to produce a constant high temperature air stream during the oxidation stage. The heterogeneous model, which considers mass and heat transport resistances in the oxygen carrier particle and the bulk fluid phase, was validated using data reported in the literature. Also, a sensitivity analysis was conducted to gain insight on system’s behaviour. Furthermore, an optimal control problem was formulated to identify optimal control profiles that can improve the efficiency of this process.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.450
Threshold uncertainty score0.753

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 head0.007
GPT teacher head0.205
Teacher spread0.198 · 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