Coke deposition and run length in industrial naphtha thermal cracking furnaces via a quasi‐steady state coupled <scp>CFD</scp> model
Bibliographic record
Abstract
Abstract Mathematical modelling of the thickness of the coke layer growing over months in millisecond cracking reactors is a dilemma in computational fluid dynamics (CFD) simulation. To address the time scale issue, a quasi‐steady state (QSS) approach was employed through a comprehensive coupled reactor/firebox CFD model in the current study. The model was applied to predict the time‐dependent behaviour of coke deposition and to determine the appropriate operating conditions for maximum olefin yields over an industrial furnace run length. A novel algorithm was designed to overcome the complexity of QSS simulation of the CFD model, which is a combination of reactive turbulence flow, combustion, and radiation models. The furnace parameters were studied as a function of two variables: the dilution steam‐to‐feed ratio and the liberated heat by the burners. The results indicated that the run length can be extended by up to 20% while retaining the main product yields. This study offers practical suggestions to maximize the run length in the operation.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".