Process modelling and simulation of bitumen partial upgrading: Analysis of solvent deasphalting‐thermal cracking configuration
Bibliographic record
Abstract
Abstract In this study, we investigate a process for partial upgrading of Canadian oil sands bitumen by means of modelling and simulation. In continuation of our previous study focused on a different process configuration for partial upgrading, the process scheme analyzed in this work consists of a solvent deasphalting step to reject asphaltenes from bitumen, a thermal cracking of the deasphalted product step, and a hydrotreating step to saturate the olefins generated by thermal cracking. The model was built using commercial simulation software, incorporating customized models for the solvent deasphalting and thermal cracking units. Trends in partial upgrader product yields and quality are examined under two operating scenarios: one where the thermal cracker operates in once‐through mode and the other where the heavy portion of the thermal cracker product is recycled. Both scenarios were observed to have difficulties in achieving the product quality targets set for partial upgrading (density <0.9400 g/cm 3 at 15.6°C and viscosity <350 cSt at 7°C) without any diluent addition. A key factor that significantly impacts final product yield and quality in this partial upgrading process is the formation of new asphaltenes during thermal cracking.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".