MétaCan
Menu
Back to cohort

Numerical Study on Heating Process of High Viscosity Crude Oil in Oil Tank of Sunken Ship

2021· article· en· W3128096954 on OpenAlexaff
Yang Shuai, Wenfeng Wu, Liu Jia, Chen Yong-yan, Wang Xuxiu

Bibliographic record

VenueIOP Conference Series Earth and Environmental Science · 2021
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsMinistry of Transportation of Ontario
Fundersnot available
KeywordsHeating oilPetroleum engineeringViscosityHeat transferCrude oilNatural convectionThermal conductionConvectionProcess (computing)Light crude oilWork (physics)Oil viscosityMaterials scienceEnvironmental scienceMechanicsWaste managementEngineeringMechanical engineeringGeologyComposite material

Abstract

fetched live from OpenAlex

Abstract This article assumes that the crude oil in the oil tank of the sunken ship is completely solidified, has high viscosity, and loses fluidity before heating. Based on ANSYS software, a three-dimensional numerical model of the sunken oil tank was constructed, and the numerical study of the heating process of high-viscosity crude oil in the sunken oil tank was carried out. According to the theory of heat transfer, the changes in the solid-liquid interface and the flow characteristics of the oil during the heating process of high-viscosity crude oil are analyzed to obtain the heat transfer characteristics during the heating process. Studies have shown that the heat transfer method at the initial stage of heating is mainly heat conduction, as the highly viscous crude oil continues to melt, the influence of natural convection gradually strengthens. This research can provide relevant theoretical basis for the underwater oil pumping work of salvaging sunken ships.

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 score0.059
Threshold uncertainty score0.473

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 studies0.0000.001
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 head0.013
GPT teacher head0.236
Teacher spread0.223 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueIOP Conference Series Earth and Environmental ScienceSame topicPetroleum Processing and AnalysisFrench-language works237,207