Further Considerations for the Determination of Service Life for Delayed Coker Drums
Bibliographic record
Abstract
Delayed coker drums are unique in hydrocarbon processing facilities in that estimating their true design and service life has been problematic. Generally, pressure containing equipment in these facilities is designed using the notion of design life based on required pressure thickness and corrosion allowance considerations. Hence, pressure containing equipment is routinely monitored by facility inspectors for wall thickness. Although many analysts have ascribed coke drum failure to “thermal stress cycling”, the difficulty posed by the operation of coke drums results in an inability to measure or calculate the magnitude of the thermo-mechanical “stresses” and the actual number of significant exposures, that is, cycles causing fatigue damage. As well, the use of Code construction practices has been generally misapplied, for this specific equipment, as the practices are intended to define a safe design life rather than a service life. Indirect measures of service life based on shell bulge severity have fallen from favor by being ineffective. A trend to use a strain index method is somewhat more appealing but is based on static load and monotonic material property considerations rather than those properties indicative of thermal cyclic operation. Recent work has shown that thermo-mechanical strain cycling can be characterized quantitatively and used to determine a cyclic service life for both undamaged and damaged coke drums. This paper discusses some of the engineering specifics to generate a high probability estimate of coke drum fatigue service life for a new drum, a damaged-stable drum, drums with weld overlay and for drums exhibiting incremental damage.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".