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Record W3164183865 · doi:10.20381/ruor-26276

CPFD Modeling of a Novel Internally Circulating Bubbling Fluidized Bed for Chemical Looping Combustion

2021· dissertation· en· W3164183865 on OpenAlexaboutno aff
C.V. McIntyre

Bibliographic record

VenueuO Research (University of Ottawa) · 2021
Typedissertation
Languageen
FieldEngineering
TopicChemical Looping and Thermochemical Processes
Canadian institutionsnot available
Fundersnot available
KeywordsChemical looping combustionFluidized bed combustionCombustionFluidizationFluidized bedNuclear engineeringMaterials scienceProcess engineeringChemical engineeringWaste managementChemistryMechanicsThermodynamicsEngineeringPhysicsPhysical chemistry

Abstract

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Pressurized chemical looping combustion (PCLC) is a promising next generation carbon capture technology which operates on the fundamentals of oxyfuel combustion to concentrate carbon dioxide in the flue gas stream. Oxygen is supplied through cyclic oxidation and reduction of a solid metal oxide between an air reactor and fuel reactor to prevent the direct contact of fuel and air. CanmetENERGY-Ottawa, in collaboration with Hatch Ltd., is designing a pilot scale PCLC system which uses ilmenite as the oxygen carrier and a novel fluidized bed design called the Plug Flow Internally-recirculating Reactor (PFIR). The PFIR consists of an annular bubbling fluidized region in which particles are circulated by angle jets through two reactive zones separated by baffles. The overall objective of this thesis was to provide key design parameters and insight for the construction of the pilot facility. Experimental work was first conducted investigating the minimum fluidization velocity (Umf), gas bubble size, and tube-to-bed heat transfer coefficients of different ilmenite particle size distributions (PSDs) at varying pressures up to 2000 kPa. The data was compared to a variety of literature correlations. The Saxena & Vogel (1977) constants for the Wen-Yu type correlations (𝑅𝑒𝑚𝑓=√𝐶12+𝐶2𝐴𝑟−𝐶1) resulted in the best fit for predicting the Umf of the PSDs with Sauter mean diameters (SMD) less than 109 μm, while the Chitester et al. (1984) constants resulted in better predictions for the larger particle size distributions (SMD greater than 236 μm). Gas bubble size was found to be marginally impacted by pressure, with the Mori & Wen (1975) correlation best fitting the data. The heat transfer coefficient was found to also be marginally increased by pressure with the the Molerus et al. (1995) correlation matching the atmospheric data. A computational particle fluid dynamic (CPFD) model of the experimental unit was then created and validated using the obtained data for minimum fluidization velocity and bubble size. The accuracy of the model was found to be dependent on the particle close packing factor input variable, with a value of 0.58 resulting in the best results for each of the ilmenite PSDs modeled. Finally, a CPFD model was created for a cold flow design of the PFIR to investigate the impacts of different operating parameters on the solids circulation rate and gas infiltration rate between the two reactor zones. This model used the validated parameters of the previous CPFD model to add confidence to the results. The impacts of increasing superficial gas velocity, fluidizing gas jet velocity, bed height, and pressure were all found to increase the solids circulation rate through their respective impacts on the momentum rate of the fluidizing gas. A polynomial function was fit between these two variables resulting in a method to predict the solids circulation rate. Similarly, the rate of gas infiltration between sections was found to be dependent on the solids circulation rate, allowing for a function to be made to predict the gas infiltration at different operating conditions.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.444
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.065
GPT teacher head0.304
Teacher spread0.239 · 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.

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

Citations0
Published2021
Admission routes1
Has abstractyes

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