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Record W1975372554 · doi:10.1115/1.4023931

A Model for Temperature Prediction for Two-Phase Oil/Water Stratified Flow

2013· article· en· W1975372554 on OpenAlexaff
Wei Shang, Cem Sarica

Bibliographic record

VenueJournal of Energy Resources Technology · 2013
Typearticle
Languageen
FieldChemistry
TopicPetroleum Processing and Analysis
Canadian institutionsCape Breton University
Fundersnot available
KeywordsHeat transferStratified flowClosure (psychology)Multiphase flowMechanicsEnvironmental scienceTwo-phase flowFlow (mathematics)Energy balancePhase (matter)Water flowControl volumeMaterials scienceThermodynamicsPetroleum engineeringEngineeringTurbulenceEnvironmental engineeringChemistry

Abstract

fetched live from OpenAlex

In this paper a mathematical model was developed to predict temperature profiles for two-phase oil-water stratified flows. Based on the energy balance of a control volume, analytical solutions were derived for the prediction of temperature profiles for two-phase oil/water stratified flow pattern in pipe flows. The model has been verified with a single-phase heat transfer model, which is available in most heat transfer textbooks. Two typical cases were simulated for extreme operating conditions with water cuts of 0% and 100%, respectively. This analytical model was also validated against experimental data. The test was conducted on a multiphase facility with accurate flow control devices and effective thermal treating units. The water cut was set at 50% for this test. The simulation results and experimental data agree within the experimental uncertainty. The closure relationships can be conveniently applied to a two-phase oil/water paraffin deposition model, which is dependent on the heat transfer process. The model was also used to predict the temperature profiles for two-phase oil and water flows with different water cuts.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.547
Threshold uncertainty score0.492

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 science0.0000.000
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 head0.009
GPT teacher head0.243
Teacher spread0.235 · 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

Citations17
Published2013
Admission routes1
Has abstractyes

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