Chloride Stress Corrosion Cracking in BFW Preheater in Reformer Unit
Bibliographic record
Abstract
Abstract Hydrogen production in a heavy oil Upgrader is one of the most important unit processes, because it provides the hydrogen and steam required for heavy oil Upgrader process facilities. These units have large heat exchanger trains which are under severe conditions such as high CO2 content and high temperatures. Therefore, the equipment in this highest impacted service are designed with highly corrosion resistant materials such as UNS S30400 and UNS S316000. However, sometimes these materials are suitable for the severe conditions of the shell side but not for the condition on the tube side. This unsuitability, in this case, is primarily due to the boiler feed water, specifically the water’s chlorine content. Even in low concentrations, chloride in the high temperature conditions in contact with austenitic material can cause a component to fail catastrophically. In addition design condition such as stress concentration devices and inappropriate commissioning procedures can make the austenitic steel tubes prone to fail too early. This paper shows the experience of failure of a heat exchanger due to chloride stress corrosion cracking (SCC) in the Upgrader facility.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 0.000 |
| 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) | 0.002 | 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".