A comprehensive sensitivity analysis on the performance of pseudo‐steady propane thermal cracking process
Bibliographic record
Abstract
Abstract The propane thermal cracking reactor process is investigated in an industrial furnace with an alternative wall burner arrangement. Temperature and heat distribution of the furnace is obtained by three‐dimensional computational fluid dynamics (CFD) simulation technique using Ansys Fluent software. Ten calculation domains are adopted to decrease calculation costs. Different fuel rate ratios are selected as the main effective parameter on reactor performance. Different ratios of base fuel rate (0.0695 kg/s) have been considered. The obtained reactor tube wall temperature profile is used for a one‐dimensional pseudo‐steady reactor operation. By the proposed new arrangement, the created coke layer thickness is lower about 3 mm compared with the base case after 700 h. Meanwhile, Propane conversion is increased by 4%. Besides, reactor feed flow rate variations are considered one of the essential parameter on reactor operation. Despite surging in propylene yield after coke formation, ethylene yield decreases during the process. By increasing the fuel rate in each reactor flow rate, ethylene increased while propylene yield descended. The maximum allowable pressure drop is 2.7 bar. At 0.5ṁ fuel rate and 0.85 kg/s reactor flow rate, pressure drop, reactor lifetime, and ethylene yield are 1.23 bar, 1444 h, and 28%; respectively. In the reactor flow of 0.85 kg/s, by raising fuel rate 0.5–2ṁ ethylene yield is increased from 28% to 46.83%, while process operating time is reduced to 780 h. According to the results, 0.8–0.85 kg/s could be considered as an appropriate range for reactor feed flow rate.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".