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Record W3009513262 · doi:10.3390/catal10030277

Virgin Heavy Gas Oil from Oil Sands Bitumen as FCC Feed

2020· article· en· W3009513262 on OpenAlexafffund
Siauw Ng, Nicole E. Heshka, Ying Zheng, Hao Ling, Jinsheng Wang, Qianqian Liu, E C Little, Fuchen Ding, Hui Wang

Bibliographic record

VenueCatalysts · 2020
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsWestern UniversityGeological Survey of CanadaNatural Resources Canada
FundersGovernment of CanadaNatural Resources CanadaSyncrude
KeywordsAsphaltOil sandsFraction (chemistry)Fluid catalytic crackingRaw materialDistillationCrackingMaterials scienceChemistryPulp and paper industryComposite materialChromatographyOrganic chemistryEngineering

Abstract

fetched live from OpenAlex

This study deals with a systematic investigation of the fluid catalytic cracking (FCC) performance of a bitumen-derived virgin heavy gas oil (HGO) in the presence of its counterpart from bitumen-derived synthetic crude oil (SCO). The objective is to determine the amelioration effect on yield and product slate by the addition of the premium SCO HGO. The 343–525 °C cut virgin bitumen HGO was obtained from distillation of a raw Athabasca oil sands bitumen. It was then blended with different amounts of the 343 °C+ fraction of commercial SCO. Four HGO blends were prepared containing 75, 64, 61, and 48 v% of SCO HGO. Each HGO blend, as well as 100% SCO HGO, were catalytically cracked at 500 and 520 °C using a bench-scale Advanced Cracking Evaluation (ACE) unit. The results show acceptable FCC performance of bitumen virgin HGO when an adequate amount of SCO HGO is added. However, the resulting liquid product may need some quality improvement before use. Several observations, including catalyst poisoning by feed nitrogen and the refractory nature of virgin HGO, are evident and help to explain some observed cracking phenomena.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 head0.012
GPT teacher head0.228
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 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

Citations8
Published2020
Admission routes2
Has abstractyes

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