Assessment of Coke Drum Materials Based on ASME Material Property Data
Bibliographic record
Abstract
Delayed coking as a part of heavy oil upgrading is characterized with severe thermal–mechanical operating conditions. Coke drums operating under such conditions require proper design and material selection in order to sustain the high stresses caused by the thermal–mechanical loading. This paper has the objective to explore alternative material selections for coke drum applications based on material property data provided in ASME Boiler & Pressure Vessel Code, Section II—Materials. The materials were compared based on the stress levels obtained by using finite element analyses (FEA) for two critical loading scenarios in the coke drum operation cycle, i.e., the heating up and quenching stages. The results show that closer matching in the coefficients of thermal expansion (CTE) between clad and base materials reduce significantly the stress in the clad during heating up stage. Among other material properties, the results show that the variation in Young's modulus values of base materials plays an important role in the variation of maximum stress in the coke drum shell during the bending of the shell caused by quenching water. Among the considered 11 pairs of clad and base material combinations, the combination of SA302-C as the base material and nickel alloy N06625 as the cladding material is recommended for delayed coke drum application.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".