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Record W2082018554 · doi:10.1016/j.egypro.2009.01.181

Foaming in amine-based CO2 capture process: Experiment, modeling and simulation

2009· article· en· W2082018554 on OpenAlexafffund
Bhurisa Thitakamol, Amornvadee Veawab, Adisorn Aroonwilas

Bibliographic record

VenueEnergy Procedia · 2009
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsUniversity of Regina
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMaterials scienceAmine gas treatingParametric statisticsAbsorption (acoustics)Aqueous solutionWork (physics)Carbon dioxideComposite materialProcess engineeringMechanical engineeringEngineeringMathematicsChemistryOrganic chemistryEnvironmental engineering

Abstract

fetched live from OpenAlex

This work provides a parametric study on foaming behavior in the carbon dioxide (CO2) absorption process using aqueous monoethanolamine (MEA) solutions. Foaming tendency was experimentally evaluated using the pneumatic method modified from ASTM standard, and reported in terms of foaminess coefficient (Σ). Results show that Σ increases and eventually decreases with MEA concentration and CO2 loading. A higher solution temperature reduces Σ. Most tested degradation products and corrosion inhibitors enhance foam tendency. A foaming model was developed to predict pneumatic steady-state foam heights. It consists of an empirical correlation for foam height prediction and a series of subroutine modules for physical property estimation. The model fits well with the experimental foam data with R2 of 0.88.

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: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
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 science0.0010.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.226
Teacher spread0.217 · 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

Citations39
Published2009
Admission routes2
Has abstractyes

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