An Approach to Determine the Initiation of Carburization in a 304H Stainless Steel Piping under Petrochemical Environment
Bibliographic record
Abstract
Abstract Carburization is a common degradation mechanism in carbonaceous gas streams at elevated temperatures in petrochemical industries. The crossover piping system between the convection section and radiant section of ethane cracking furnaces is fabricated from 304H stainless steel (SS), and is normally protected by a chromium oxide layer. Carburization (and potentially metal dusting) forms once degradation of the oxide layer occurs during the ethane cracking/decoking process. A thorough metallurgical analysis demonstrated that some components of the crossover piping system in one of our plants suffered from carburization and metal dusting. This paper describes a methodology developed to determine the initiation point of carburization based on metallurgical analysis and theoretical modeling. The predicted initiation point of carburization, using this approach, was correlated with a major process parameter change in the plant operation, which greatly reduced the protection of the aged 304H SS from carburization and metal dusting. Fick’s Second Law of Diffusion was applied to describe carbon diffusion kinetics into the bulk pipe steel, the heat-affected zone (HAZ) and the weld. It has been established through metallurgical analysis that depth of carburization of this particular pipe section followed a power-law relationship with carburization times (in the unit of years). These relationships can be used to ascertain the initiation point of carburization for the HAZ and the bulk steel, thus providing important information for life assessment of this crossover piping system.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 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 | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".