Multiobjective particles swarm optimization and multicriteria decision making of improved cumene production process including economic, environmental, and safety criteria
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Cumene is one of the five chemicals with the highest production in the world. In this work, the design by Flegiel was improved to increase the production rate of the cumene process by adding a trans‐alkylation reactor, then multi‐objective optimization (MOO) using the particles swarm optimization (PSO) algorithm is used to improve the process design. Furthermore, seven multicriteria decision‐making (MCDM) methods for selecting an optimal solution from the Pareto‐optimal front related to two MOO problems were performed. In this optimization, conflicting objectives such as total capital cost (TCC), energy cost, wastage rate, and safety target are simultaneously minimized in the format of trade‐offs. Finally, the results of this work were compared with those reported designs. The optimal solution chosen by MCDM methods is at TCC = 5589, damage index (DI) = 0.044, and material loss = 0.0005.
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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