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Record W4389139761 · doi:10.1115/pvp2023-101378

Creep Property of Type 316Cb Stainless Steel Heater Tube

2023· article· en· W4389139761 on OpenAlexaff
Jorge L. Hau, Bing Hsieh, Neil Park

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicHigh Temperature Alloys and Creep
Canadian institutionsShell (Canada)
Fundersnot available
KeywordsCreepMaterials scienceTube (container)MetallurgyMicrostructureService lifeComposite material

Abstract

fetched live from OpenAlex

Abstract A metallurgical evaluation was conducted involving a 316Cb tube removed from an atmospheric distillation unit heater, after 18 years of service. Since this steel is not a standard material for heater tubes, the design used creep properties from type 347 stainless steel tube. A tube sample was submitted for remaining life assessment. The material properties reported for type 347H stainless steel were used for this study. The creep tests were conducted following the Omega method, but LMP data were also derived to make an assessment based on this method as well. Applying both methods, the type 316Cb steel appeared creep stronger than 347H steel. The 316Cb steel in this tube sample did not undergo significant microstructure degradation and creep life consumption, thus, estimation indicated ample remaining life for future service. Type 316H steel was not used as reference because the original design used type 347 stainless steel tube properties to determine the required wall thickness.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.002
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0020.000

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 head0.012
GPT teacher head0.208
Teacher spread0.196 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2023
Admission routes1
Has abstractyes

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