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Record W7008506500

CO<sub>2</sub> Capture With MEA: Integrating the Absorption Process and Steam Cycle of an Existing Coal-Fired Power Plant

2006· dissertation· en· W7008506500 on OpenAlexaffabout

Bibliographic record

VenueUWSpace (University of Waterloo) · 2006
Typedissertation
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsBlackberry (Canada)University of Waterloo
Fundersnot available
KeywordsFlue gasPower stationWaste heatCombined cycleAbsorption (acoustics)Process (computing)Thermal power stationSensitivity (control systems)Flue
DOInot available

Abstract

fetched live from OpenAlex

In Canada, coal-fired power plants are the largest anthropogenic point sources of atmospheric CO2. The most promising near-term strategy for mitigating CO2 emissions from these facilities is the post-combustion capture of CO2 using MEA (monoethanolamine) with subsequent geologic sequestration. While MEA absorption of CO2 from coal-derived flue gases on the scale proposed above is technologically feasible, MEA absorption is an energy intensive process and especially requires large quantities of low-pressure steam. It is the magnitude of the cost of providing this supplemental energy that is currently inhibiting the deployment of CO2 capture with MEA absorption as means of combatting global warming. \nThe steam cycle of a power plant ejects large quantities of low-quality heat to the surroundings. Traditionally, this waste has had no economic value. However, at different times and in different places, it has been recognized that the diversion of lower quality streams could be beneficial, for example, as an energy carrier for district heating systems. In a similar vein, using the waste heat from the power plant steam cycle to satisfy the heat requirements of a proposed CO2 capture plant would reduce the required outlay for supplemental utilities; the economic barrier to MEA absorption could be removed. \nIn this thesis, state-of-the-art process simulation tools are used to model coal combustion, steam cycle, and MEA absorption processes. These disparate models are then combined to create a model of a coal-fired power plant with integrated CO2 capture. A sensitivity analysis on the integrated model is performed to ascertain the process variables which most strongly influence the CO2 energy penalty. From the simulation results with this integrated model, it is clear that there is a substantial thermodynamic advantage to diverting low-pressure steam from the steam cycle for use in the CO2 capture plant. During the course of the investigation, methodologies for using Aspen Plus® to predict column pressure profiles and for converging the MEA absorption process flowsheet were developed and are herein presented.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.005
GPT teacher head0.181
Teacher spread0.176 · 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 designSimulation or modeling
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
Published2006
Admission routes2
Has abstractyes

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