Modeling and Optimization of the Upgrading and Blending Operations of Oil Sands Bitumen
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Bibliographic record
Abstract
A general framework is proposed for the operation optimization of a bitumen upgrading plant in the oil sands industry. On the basis of simulation results from an upgrading plant in an Aspen HYSYS environment, empirical models are developed through statistical analysis for different process units. Each generated correlation is a function of the relevant process unit operating conditions. All of the correlations are further used to develop the upgrading plant optimization model, which is a non-convex nonlinear optimization (NLP) problem. The proposed model is tested on three examples in which different commodity demands are imposed as constraints: (i) no restriction for production, (ii) sweet synthetic crude oil (SCO) production, and (iii) mandatory multiple production. Results demonstrate the efficacy of the proposed framework for the upgrading plant operation optimization.
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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 it