The Influence of Naphthenic Acid and Sulfur Compound Structure on Global Crude Corrosivity under Vacuum Distillation Conditions
Bibliographic record
Abstract
Abstract At temperatures between 220 and 400°C, naphthenic acid and sulfur-containing species present in many global crudes are known to cause refinery corrosion. Naphthenic acids are organic acids often described as cycloalkane ring(s) with an attached aliphatic chain having a terminal carboxylic acid group. Elemental sulfur, mercaptan, sulfide and polysulfide species convert to hydrogen sulfide which attacks metal. However, neither total acid contents measured by total acid number (TAN) nor total sulfur contents measured by elemental analyses have been found to correlate well with corrosivity. A fundamental study of the relationships of molecular structures of organic acid and sulfur compounds to corrosivity has been performed in a test unit that simulates corrosion found under vacuum distillation conditions. The corrosivities of model oil mixtures consisting of specific organic acid compounds in the presence or absence of specific sulfur compounds in white oil were measured. The corrosivities of global crudes including Athabasca are discussed in terms of their contents of different types of organic acid and sulfur species. In particular, analyses of coupon surfaces and crude oil organic acid subspecies identify the most corrosive species. This work was partially supported by the Canadian Association of Petroleum Producers and Alberta Innovates - Energy and Environment Solutions (formerly Alberta Energy Research Institute).
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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 | 0.001 |
| 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) | 0.001 | 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".