Petroleum coke gasification: A review
Bibliographic record
Abstract
Abstract The production of petroleum coke (petcoke) in the refineries is progressively peaking up because of the trend of processing heavy crudes and in turn, a renewed interest in delayed coking process. Therefore, an efficient, economical, and environmentally safe utilisation of petcoke has become imperative in the current petroleum refining scenario. Gasification of petcoke has emerged as one of the attractive options and is gaining increasing attention to convert the petcoke to value‐added products. The process offers the refiners a variety of product slates mainly via synthesis gas route. The products include steam, hydrogen, electricity, chemicals (viz. methanol, ammonia, etc.), liquid fuels via Fischer–Tropsch (F‐T) synthesis and so on. Petcoke has been identified as a potential feedstock for about 15% of the total planned gasification capacity worldwide. In the present communication, the published literature pertaining to petcoke gasification has been extensively analysed and a state‐of‐the‐art review has been written that includes: (1) the importance of petcoke gasification in the present petroleum refining scenario; (2) petcoke gasification reaction mechanism, kinetics, and typical product profile; (3) parametric sensitivity of the operating variables such as temperature and pressure; (4) various gasifiers for petcoke gasification; (5) modelling efforts on different types of gasifiers and (6) future prospects of petcoke gasification. An attempt has been made to get the afore‐mentioned aspects together in a thematic framework so that the information is available at a glance and is expected to be useful as a single point source to the researchers and practicing refiners.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.002 |
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".