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Record W3087565850 · doi:10.1002/cjce.23880

A heat‐transfer model for tube fouling in the radiant section of once‐through steam generators

2020· article· en· W3087565850 on OpenAlexafffundvenueabout
Steven D. Herman, Anil K. Mehrotra

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicHeat Transfer and Boiling Studies
Canadian institutionsUniversity of Calgary
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsFoulingHeat transferTube (container)Shell and tube heat exchangerConvectionThermal conductivityWaste managementMaterials sciencePetroleum engineeringNuclear engineeringEnvironmental scienceChemistryMechanicsComposite materialEngineering

Abstract

fetched live from OpenAlex

Abstract Once‐through steam generators (OTSGs) produce steam by recycling produced water in the steam‐assisted‐gravity‐drainage (SAGD) process for extracting Alberta's oil sands via in situ recovery of bitumen. The industry's specifications for water quality, steam quality, and water recycle ratio, as well as high temperature and pressure operations, lead to the fouling of OTSG tubes, which has important economic, safety, and environmental consequences. The roles and mechanisms of inorganic and organic impurities on tube fouling also complicate the study of heat transfer in OTSGs. Heat transfer in OTSGs involves radiation, convection, conduction, forced convection, and boiling. In this investigation on OTSG fouling, a steady‐state mathematical model was built in Microsoft Excel, incorporating industry design data, to demonstrate the impact of tube fouling on heat transfer and tube‐wall temperature. The model predictions indicate that tube fouling introduces a significant thermal resistance that not only decreases the rate of heat transfer but also causes an increase in the tube‐wall temperature such that it could exceed the safe operating limits of the tube material, leading to potential tube failures . Predictions are provided for the average tube‐wall temperature exceeding the recommended operating limit of 700 K over a range of foulant thermal conductivity (ie, 0.05‐2 W m −1 K −1 ) and foulant thickness (ie, 0.4‐11 mm corresponding to 0.1%‐30% of the tube radius).

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.076
Threshold uncertainty score0.354

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 head0.027
GPT teacher head0.206
Teacher spread0.179 · 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 designSimulation or modeling
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

Citations6
Published2020
Admission routes4
Has abstractyes

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