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Record W2024641441 · doi:10.1081/lft-200048166

Flow Enhancement of Medium-Viscosity Crude Oil

2006· article· en· W2024641441 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePetroleum Science and Technology · 2006
Typearticle
Languageen
FieldEngineering
TopicFluid Dynamics and Mixing
Canadian institutionsConcordia University
FundersUnited Arab Emirates University
KeywordsViscosityFlow (mathematics)Crude oilChemistryFlow propertiesChromatographyPetroleum engineeringThermodynamicsMechanicsGeologyPhysics

Abstract

fetched live from OpenAlex

Abstract This study investigated the different alternatives to enhance the flowability of crude oil with medium viscosity. These alternatives include the addition of water into crude oil to form water-in-oil emulsion, the addition of light petroleum product, the addition of flow improver, and a preheating technique. Temperature range of 10–50°C, water concentration range of 0–50% by volume, flow improver concentration range of 0–5000 ppm, and kerosene concentration range of 0–50% by volume were investigated in the flowability enhancement study of crude oil with medium viscosity. The flowability enhancement in terms of viscosity reduction was investigated using RheoStress RS100 from Haake. A cone–plate sensor was used with a cone angle of °4, cone diameter of 35 mm, and 0.137-mm gap at the cone tip. The addition of kerosene to crude oil improves the flowability much better than any other investigated technique.

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.

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 score0.449
Threshold uncertainty score0.279

Codex and Gemma teacher scores by category

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

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 head0.003
GPT teacher head0.181
Teacher spread0.178 · 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