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Record W2043051042 · doi:10.1115/1.4029958

Assessment of Coke Drum Materials Based on ASME Material Property Data

2015· article· en· W2043051042 on OpenAlexaff
Milan Nikic, Zihui Xia, Pierre Du Plessis

Bibliographic record

VenueJournal of Pressure Vessel Technology · 2015
Typearticle
Languageen
FieldMaterials Science
TopicHydrogen embrittlement and corrosion behaviors in metals
Canadian institutionsSuncor Energy (Canada)University of Alberta
Fundersnot available
KeywordsCokeDrumMaterials scienceMetallurgyMaterial propertiesFinite element methodThermalComposite materialCladding (metalworking)Boiler (water heating)Stress (linguistics)Structural engineeringMechanical engineeringWaste managementEngineering

Abstract

fetched live from OpenAlex

Delayed coking as a part of heavy oil upgrading is characterized with severe thermal–mechanical operating conditions. Coke drums operating under such conditions require proper design and material selection in order to sustain the high stresses caused by the thermal–mechanical loading. This paper has the objective to explore alternative material selections for coke drum applications based on material property data provided in ASME Boiler & Pressure Vessel Code, Section II—Materials. The materials were compared based on the stress levels obtained by using finite element analyses (FEA) for two critical loading scenarios in the coke drum operation cycle, i.e., the heating up and quenching stages. The results show that closer matching in the coefficients of thermal expansion (CTE) between clad and base materials reduce significantly the stress in the clad during heating up stage. Among other material properties, the results show that the variation in Young's modulus values of base materials plays an important role in the variation of maximum stress in the coke drum shell during the bending of the shell caused by quenching water. Among the considered 11 pairs of clad and base material combinations, the combination of SA302-C as the base material and nickel alloy N06625 as the cladding material is recommended for delayed coke drum application.

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)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.025
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0020.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.054
GPT teacher head0.331
Teacher spread0.277 · 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.

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

Citations5
Published2015
Admission routes1
Has abstractyes

Explore more

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