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Record W2545380743 · doi:10.20381/ruor-20017

Fluidized Bed Combustion with Integrated Carbon Dioxide Capture

2010· dissertation· en· W2545380743 on OpenAlexaboutno aff
Robin W. Hughes

Bibliographic record

VenueuO Research (University of Ottawa) · 2010
Typedissertation
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsnot available
Fundersnot available
KeywordsCarbon dioxideCombustionFluidized bedWaste managementFluidized bed combustionEnvironmental scienceCarbon capture and storage (timeline)Process engineeringEngineeringChemistryClimate changeGeology

Abstract

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The connection between increasing atmospheric CO2 concentrations and climate change is now recognized by a number of international organizations including the United Nations Fran1ework Convention on Climate Change (UNFCCC), the Intergovernmental Panel on Climate Change (White et al, 2003), and the European Union FP6 Framework. The research described in this thesis brings two carbon dioxide capture technologies from concept through to bench scale testing, simulation, and demonstration at pilot scale. Facilities for demonstrating and investigating oxy-fuel circulating fluidized bed combustion with recycled flue gas and and calcium-based sorbent looping cycles are developed and described. The facilities were commissioned with coal and biomass. It is shown that high CO2 concentration 10 the calciner is highly detrin1ental to the performance of the sorbent Hydration of the sorbent can greatly improve the capacity of the sorbent when relatively low CO 2 concentrations are present, however, when CO2 concentration is high there is little difference between untreated and hydrated sorbent capacity after 20 cycles. Steam hydration together with pelletization of limestone was used to improve sorbent utilization for in-situ CO 2 capture under operating conditions typical of fluidized bed combustion. The pelletized particles in general showed good performance, comparable to or better than hydrated san1ples. Attrition of the sorbents has been greater than expected for some of the limestones. The results suggest that multiple carbonation/calcination cycles result in severe attrition during the first one or two calcination periods. Afterwards, the particles attrite at rates similar to what would be expected from a bed of particles continuously subjected to similar forces over an extended period of time. In limestones where material loss is a problem, however, it is clear that partial sulphation can dramatically reduce this loss, albeit with the risk of reduction of CO2 carrying capacity or CaO-CaCO3 looping cycle reversibility. Sorbent capacity was significantly lower than expected based on previous thermogravimetric analyses. A thin, non-porous shell was formed around the sorbent particles under some of the test conditions at the pilot scale. The causes for the formation of this shell must be verified prior to investing substantially in this technology as the shell greatly reduces the capacity of the sorbent. The fact that the shell was not formed in all tests provides hope that a suitable set of conditions can be found for operation where the shell does not hinder sorbent performance. The calcium-based sorbent looping cycle process has been demonstrated using the CANMET 75 kWth pilot-scale dual fluidized bed facility and more than 50 hrs operating experience in total has been accumulated. Havelock limestone from eastern Canada was used as the CO2 sorbent, while a synthesis gas mixture of air and CO2 (15%) was employed to simulate combustion flue gas. A high CO2 capture efficiency (> 95%) was achieved for the first several cycles, which decreased to a lower level (> 72%) after more than 25 cycles. Oxy-fuel combustion of biomass and coal was employed in the sorbent regeneration step, in which pure O2 was mixed with recycled flue gas and this, along with the excellent heat transfer characteristics of CFBs, allowed the use of an O2 concentration of 40 vol% in the combustion gas.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
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 score0.004
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.012
GPT teacher head0.234
Teacher spread0.221 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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
Published2010
Admission routes1
Has abstractyes

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