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Record W2901714850 · doi:10.1021/acs.iecr.8b03983

Quantification of Mutual Mass Transfer of CO<sub>2</sub>/N<sub>2</sub>–Light Oil Systems by Dynamic Volume Analysis

2018· article· en· W2901714850 on OpenAlexafffund
Xiaomeng Dong, Yu Shi, Daoyong Yang

Bibliographic record

VenueIndustrial & Engineering Chemistry Research · 2018
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsUniversity of Regina
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsDiffusionVolume (thermodynamics)ChemistryMass transferLight crude oilAnalytical Chemistry (journal)Gaseous diffusionThermodynamicsMass transfer coefficientSolubilityMolecular diffusionGas oil ratioPhase (matter)ChromatographyOrganic chemistryPhysical chemistry

Abstract

fetched live from OpenAlex

A novel and pragmatic method has been developed to quantify mutual mass transfer between a gas (e.g., CO 2 and N 2 ) and light oil by dynamic volume analysis. Experimentally, diffusion experiments for pure CO 2 /N 2 -light oil systems are conducted at a constant pressure and temperature with a pressure/volume/temperature (PVT) system. During the diffusion experiments, the diluted volume of oil phase is continuously monitored and recorded, while gas samples are collected at the end of the diffusion tests to measure gas compositions by performing gas chromatography (GC) analysis. Theoretically, the mass transfer from light oil to gas phase and the solubility of a gas into the light oil is quantified by combining the GC analysis and Fick’s second law, while the Peng–Robinson equation of state is employed to determine the concentration of each gas component in the oil phase by imposing the quasi-equilibrium boundary condition at the gas–oil interface. The diffusion coefficient of each component can be determined once the discrepancy of both the swelling factor and the gas composition between the experimental measurements and the calculated ones are minimized. At temperature of 336.15 K, the diffusion coefficients of carbon dioxide and nitrogen are determined to be 12.87 × 10 –9 m 2 /s at pressure of 2170 kPa and 1.35 × 10 –9 m 2 /s at pressure of 5275 kPa, respectively. For the diffusion coefficient of light oil to the gas phase, it is determined to be 6.04 × 10 –11 m 2 /s for the CO 2 -light oil system and 2.55 × 10 –12 m 2 /s for the N 2 -light oil system under the corresponding conditions. Furthermore, the dynamic swelling factor of oil in the CO 2 -light oil system is measured to be higher than that of the N 2 -light oil system. The GC analysis confirms that there exists light-component extraction, though the concentration is small in this study since the experimental pressure is below the critical pressure of 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)0.001
metaresearch head score (Gemma)0.001
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 score0.001
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
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 head0.028
GPT teacher head0.274
Teacher spread0.246 · 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

Citations38
Published2018
Admission routes2
Has abstractyes

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