MétaCan
Menu
Back to cohort

Density and Viscosity of Multicomponent Solvent (<i>n</i>-Pentane + <i>n</i>-Hexane + <i>n</i>-Heptane + <i>cyclo</i>-Hexane + Toluene) and Bitumen Mixtures─Implications for In Situ Bitumen Recovery and Transportation of Diluted Bitumen

2023· article· en· W4389986355 on OpenAlexafffund
Mohammad S. Khan, Hassan Hassanzadeh

Bibliographic record

VenueEnergy & Fuels · 2023
Typearticle
Languageen
FieldEngineering
TopicPhase Equilibria and Thermodynamics
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of Calgary
KeywordsAsphaltTolueneHexanePentaneHeptaneViscositySolventDiluentChemistryGreenhouse gasOil sandsPetroleum engineeringMaterials scienceOrganic chemistryComposite materialGeology

Abstract

fetched live from OpenAlex

Conventional techniques for extracting and transporting bitumen, such as steam-assisted gravity drainage (SAGD), are associated with significant environmental drawbacks and contribute to greenhouse gas emissions. Embracing alternative processes could significantly mitigate these environmental impacts significantly. Furthermore, developing more energy-efficient extraction and transportation methods holds the potential to reduce energy consumption and associated carbon emissions, contributing to a more sustainable energy sector. This study introduces novel measurements pertaining to the thermophysical properties of a multicomponent synthetic solvent ( n -pentane + n -hexane + n -heptane + cyclo -hexane + toluene) and bitumen mixtures within a pressure range extending up to 8.769 MPa and temperatures reaching up to 389 K. This information is of utmost significance in the design, optimization, and simulation of in situ recovery methods. Moreover, the measured properties are crucial in the design of surface processing and transport of diluted bitumen. Empirical relationships are established to determine the thermophysical properties of the studied multicomponent systems. These correlations, yielding average absolute relative deviations (AARD) of 0.36% for density and 8.81% for viscosity, offer simple tools for estimation of these properties in multicomponent systems composed of bitumen and synthetic diluent. Our results illustrate that the utilization of a synthetic diluent for viscosity reduction leads to a corresponding reduction in greenhouse gas emissions and results in significant energy savings. The results hold relevance across a spectrum of applications, spanning solvent-based bitumen recovery processes, surface treatments, and the efficient transportation of bitumen via pipelines.

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)0.001
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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.010
GPT teacher head0.220
Teacher spread0.210 · 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

Citations3
Published2023
Admission routes2
Has abstractyes

Explore more

Same venueEnergy & FuelsSame topicPhase Equilibria and ThermodynamicsFrench-language works237,207