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Record W4385066547 · doi:10.1002/cjce.25045

Investigation of solid particle erosion‐related failures in once‐through steam generators (<scp>OTSGs</scp>) in oil sands in‐situ production: The limitations of the <scp>API RP 14E</scp> guideline in <scp>OTSG</scp> design or operational decision‐making

2023· article· en· W4385066547 on OpenAlexafffundvenue
Oluwaseun Ezekiel Adedeji, Anupam Kumar, Basil Perdicakis, R. Sean Sanders

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicErosion and Abrasive Machining
Canadian institutionsSuncor Energy (Canada)University of Alberta
FundersNatural Sciences and Engineering Research Council of CanadaCanada's Oil Sands Innovation Alliance
KeywordsBoiler (water heating)Steam-assisted gravity drainageOil sandsPetroleum engineeringCorrosionSteam injectionEnvironmental scienceGravity separationWaste managementMetallurgyEngineeringMaterials scienceEnvironmental engineeringComposite material

Abstract

fetched live from OpenAlex

Abstract The required steam for steam‐assisted gravity drainage (SAGD) oil sands operations is generated using a once‐through steam generator (OTSG) that is fed with relatively poor quality process water. Industries have reported possible solid particle erosion‐related failure in the OTSG boiler tubes because of the transport of precipitated dense inorganic particles. However, the presence of other damage mechanisms, e.g. corrosion, flow accelerated corrosion (FAC), often masks the evidence of erosive wear. Also, industries set an upper limit operating velocity for the OTSG using the API RP 14E guideline, which provides no quantitative erosion rates to determine an operating envelope. This study presents a computational fluid dynamics (CFD) analysis of erosion damage in a SAGD OTSG boiler tube. The results revealed that API RP 14E may not be an effective decision‐making tool for operating the OTSG system. For example, a 10% increase in velocity, even at conditions below the API RP 14E threshold, showed a decrease in the failure time of the boiler tubes by 40%–50%.

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)0.002
metaresearch head score (Gemma)0.008
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 score0.485
Threshold uncertainty score0.926

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.043
GPT teacher head0.250
Teacher spread0.207 · 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

Citations8
Published2023
Admission routes3
Has abstractyes

Explore more

Same venueThe Canadian Journal of Chemical EngineeringSame topicErosion and Abrasive MachiningFrench-language works237,207