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Record W4404369776 · doi:10.1115/pvp2024-122815

Indicators for Coke Drum Replacement Due to Bulge-Induced Damage

2024· article· en· W4404369776 on OpenAlexaff
Egler Dubin Araque Vivas, Stephen M. Park

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnergy
TopicCoal and Coke Industries Research
Canadian institutionsCanadians Living with HIV
Fundersnot available
KeywordsDrumCokeBulgeMaterials scienceComputer scienceMetallurgyEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Replacement of coke drums is a major project that requires a significant investment and at least 3 or 4 years of planning. One of the leading causes of drum replacement has been the cost associated with repairs and unexpected shutdowns due to bulge-induced damage. An assessment of the total area of bulge-induced damage in 10 coke drums from two refineries (Sites A and B) that are conducting replacement projects is shown as an example of parameters that can be identified and tracked over the life span of the vessel. The Local Plastic Strain Indicator, abbreviated as LPSI, is used as a methodology to quantify and track the evolution of bulged areas and surface damage found during laser mapping and remote visual inspections. LPSI identifies and ranks bulges prone to local failures using plastic strain calibrated against bulges that developed internal or external bulge-induced damage. The LPSI is the ratio of the plastic strain found at the point being analyzed to the calibrated strain limit found at points where through-wall cracks occurred due to bulging, in a percentage form. Using LPSI to find the surface area of the drum cylinder that is bulged is a novel concept. Results show how total bulged area and the area with elephant skin surface damage increases over time, reaching the point where repairs are required to stop bulge growth and maintain safe operations. Eventually the accumulated bulging, surface damage, and amount of repairs required reach the point where the cost and potential for unexpected shutdowns leads to vessel replacement. Examples are provided to assist refiners in understanding how to assess their own 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 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)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.006

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0050.002
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.037
GPT teacher head0.327
Teacher spread0.290 · 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 designObservational
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
Published2024
Admission routes1
Has abstractyes

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