C-½Mo Vs 1Cr-½Mo: A Comparative Study of Coke Drum Shell Materials
Bibliographic record
Abstract
Abstract To mitigate the impact of severe thermal loads during operation, two different design methodologies are typically adopted when selecting base metal materials for coke drum fabrication. The first approach favors the use of certain chromoly steels (i.e. 1¼Cr and higher), prioritizing strength characteristics to improve resistance to bulging. The second approach, which favors carbon steel and C-½Mo, acknowledges the inevitability of bulging and targets materials with lower strength and finer grain size to optimize fracture ductility, allowing larger bulges to develop before cracking occurs. The trade-off between optimizing bulge resistance and cracking resistance is a critical consideration, particularly when other factors, such as the superior reparability of C-½Mo, may influence material selection. This study examines eight coke drums from the same upgrader unit that were designed using “lower strength” base metal materials; six were fabricated using a C-½Mo alloy, two were fabricated using a 1Cr-½Mo alloy. Despite differences in material composition, both sets of drums share many design and operating characteristics, providing an ideal framework for directly comparing the two base metal materials. An extensive experimental testing program was conducted on boat samples extracted from all eight coke drums, along with a review of historical inspection data. Based on the performance metrics outlined in this study, the C-½Mo drums generally outperform their 1Cr-½Mo counterparts.
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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) | 0.000 | 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) | 0.001 | 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".