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Record W2605935935 · doi:10.1002/cjce.22873

Thermo‐physical properties of <i>n</i>‐pentane/bitumen and <i>n</i>‐hexane/bitumen mixture systems

2017· article· en· W2605935935 on OpenAlexafffundvenue
Ali Haddadnia, Mohsen Zirrahi, Hassan Hassanzadeh, Jalal Abedi

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2017
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsAsphaltPentaneViscosityHexaneSolventMixing (physics)ThermodynamicsChemistryMaterials scienceOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

The gravity drainage as a result of viscosity reduction is the main governing mechanism of the solvent‐aided thermal bitumen recovery processes. Therefore, the density and viscosity of the diluted or heated bitumen are essential to predict the oil production rate. In this paper, we report thermo‐physical properties of n ‐pentane/bitumen and n ‐hexane/bitumen mixtures. The density and viscosity of Athabasca bitumen diluted with n ‐pentane and n ‐hexane were measured at different temperatures (30 to 190 °C), pressures (2 to 8 MPa), and solvent mass fractions (0.05 to 0.5). Various correlations and mixing rules proposed in the literature were examined to calculate the density and viscosity of the diluted bitumen. This study proposes appropriate mixing rules and generalized parameters for predicting the density and viscosity of solvent‐bitumen systems. Our findings will find applications in the design and simulation of heavy oil and bitumen solvent‐aided thermal recovery processes.

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 score0.012
Threshold uncertainty score0.454

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 science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.009
GPT teacher head0.186
Teacher spread0.177 · 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

Citations25
Published2017
Admission routes3
Has abstractyes

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