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Record W2884179986 · doi:10.1680/jenge.18.00012

Modelling of ex situ dissolution for CO<sub>2</sub> sequestration

2018· article· en· W2884179986 on OpenAlexafffund
Aleksander Cholewinski, Yuri Leonenko

Bibliographic record

VenueEnvironmental Geotechnics · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicCO2 Sequestration and Geologic Interactions
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDissolutionCarbon dioxideLaminar flowDiffusionTurbulent diffusionTurbulenceBrineMaterials scienceMechanicsChemistryChemical engineeringThermodynamicsPhysicsEngineering

Abstract

fetched live from OpenAlex

In this paper, a model for diffusion-controlled dissolution of carbon dioxide (CO 2 ) droplets is presented. This model is applied to a system of co-current turbulent horizontal pipe flow of carbon dioxide–brine mixture in order to determine the feasibility of dissolving carbon dioxide within the pipe before injecting underground. Depending on the droplet size, there are two regimes of dissolution within the pipe: turbulent for large droplet size and laminar (pure diffusion) for smaller sizes. Since the droplet (while dissolving and therefore shrinking in size) may undergo both regimes, the droplet size at which it transitions from turbulent to diffusion-controlled dissolution is estimated and used to find the total time spent in diffusion-controlled dissolution regime. It was observed that diffusive dissolution is of similar order of magnitude to turbulent dissolution, and so both mechanisms must be taken into account in the evaluation of the total dissolution time. This diffusive dissolution time should be combined with the time spent in the turbulent regime to determine time pipe lengths required for complete dissolution of carbon dioxide droplets.

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)0.000
Version: codex-gemma-dda1882f352aValidation 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 score0.246
Threshold uncertainty score0.641

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)0.0010.000

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 head0.024
GPT teacher head0.247
Teacher spread0.224 · 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.

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

Citations1
Published2018
Admission routes2
Has abstractyes

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