Determination of Service Life for Undamaged and Damaged Delayed Coker Drums
Bibliographic record
Abstract
A stated goal of governments in addressing climate warming and to transition to a low carbon future by the end of this century is to increase the proportion of energy supplied by alternative sources. For the hydrocarbon processing industry, the question of stranded assets will become significant as these alternative energy sources become more prevalent. Existing equipment will need to operate to the end of its useful life and new equipment may need to be avoided. In particular, coker drums are very expensive investments due to their size, materials and number required in the delayed coker unit of a processing facility. Because of the severe service environment in which coke drums operate, the service life of a drum is not well established. Long term reliability of coker drums is impacted by thermo-mechanical damage mechanisms associated with self constraint of the drum shell and skirt during the formation of hot and cold temperature spots and patches. By assessing the imposed thermomechanical strains, a more precise determination of drum fatigue may be made, allowing better estimation of service life. This service life may be estimated for newly fabricated drums and those drums with shell damage, such as bulging. Service life determination is of practical importance for operators since it provides a more realistic estimate of operational life as compared to the normally referenced Code design life. An accurate estimation of drum service life has not been available in the industry to date due to a number of deficiencies and conservatisms in the current calculation practices. Insight into the causal damage mechanism provides opportunities in identifying alternatives in design, material selection, fabrication, inspection, and maintenance for operating this equipment to a practical and optimal target service life.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".