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Record W4409501138 · doi:10.5006/c2023-19182

Coke Drum Weld Design for Better Fatigue Performance

2023· article· en· W4409501138 on OpenAlexaff
Haixia Guo, Mark E. Odegard, Enzo Falo, Simon Yuen

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicMetal Alloys Wear and Properties
Canadian institutionsSuncor Energy (Canada)
Fundersnot available
KeywordsDrumCokeWeldingMaterials scienceMetallurgyComputer scienceMechanical engineeringEngineering

Abstract

fetched live from OpenAlex

Abstract Low cycle fatigue is a dominating damage mechanism for coke drums due to the batch cyclic operation and water quenching process. Resistance to low cycle fatigue is one of the major considerations when designing new drums. In a major coke drum replacement project, lab testing was employed to assist selection of weld profile, welding processes for clad restoration, and to generate the fatigue curves for the specific weld design. This paper summarizes part of the main testing results and findings from the lab testing program, using samples made with C-0.5Mo steel with Alloy 625 cladding. These testing results supported design selection for better fatigue resistance and are anticipated to increase service life of the new coke drums.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score0.087
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.003

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 head0.133
GPT teacher head0.282
Teacher spread0.149 · 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; both teacher heads agree on what is shown here.

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

Citations2
Published2023
Admission routes1
Has abstractyes

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