Enhancement of petroleum coke thermal reactivity using Oxy‐cracking technique
Bibliographic record
Abstract
Petroleum coke (petcoke) is a challenging fuel in terms of its complexity, high sulphur and nitrogen content, low volatile content, and undesirable emissions of SOx and NOx when used for power generation. To overcome these challenges, the oxy‐cracking process was recently proposed to convert the petcoke into a clean combustion fuel by reducing its sulphur and nitrogen contents, and consequently increasing its reactivity and combustibility. This work aimed to study the heating values and thermo‐oxidative behaviour of the oxy‐cracked petcoke, virgin petcoke, and their blends using thermogravimetric analysis (TGA). The results showed that the oxy‐cracked petcoke is oxidized at a temperature of 475 °C, which is easier and faster than the virgin petcoke, which is usually oxidized at around 540 °C. The heating value of the oxy‐cracked petcoke was not impacted and maintained constant ~30 MJ/kg, which is relatively similar to the virgin petcoke. The nitrogen and sulphur content in the oxy‐cracked petcoke is much lower than that of virgin petcoke. A significant improvement in the combustion performance parameters of the oxy‐cracked petcoke and their blends with virgin petcoke was achieved. For instance, the ignition temperature of the proposed fuel is reduced to 13 % compared to the virgin petcoke, which led to increasing the ignition index by two‐folds. Therefore, this approach might help in improving the thermal efficiency of petcoke by using oxy‐cracked products as an initiator in the combustion process.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".