Alternative Selections of Delayed Coke Drum Materials Based on ASME Material Property Data
Bibliographic record
Abstract
Severe cyclic thermo-mechanical operating conditions during delayed coking can cause damages in the form of bulging and cracking in coke drums. As a result, the industry has to perform costly repairs and maintenance shutdowns. Therefore, it is important to understand the damage and failure mechanisms of the coke drums and to achieve more reliable coke drum design solutions. This paper explores alternative selections of clad and base material combinations for coke drum applications based on material property data provided in ASME Boiler & Pressure Vessel Code, Section II - Materials. Finite element analyses are carried out by simulating two critical loading scenarios in the coke drum operation cycle, i.e. the heating up and quenching stages. The analysis results show that the major achievement in lowering the stress level in the clad layer is due to matching of the coefficients of thermal expansion between clad and base materials. In addition, the finite element analyses indicate that the differences in Young’s modulus values play an important role in the variation of maximum stress in the coke drum shell during the quenching stage. Among eleven pairs of the clad and base material combinations studied, the combination of SA302-C as the base and nickel alloy N06625 as the cladding material is recommended.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".