Rigorous design and control of thermally integrated pressure‐swing reactive distillation process for isobutyl acetate production considering the effect of column pressures
Bibliographic record
Abstract
Abstract By studying the effect of pressure on relative volatility, azeotrope composition, and net reaction rate, a rigorous pressure‐swing thermally integrated reactive distillation (PST‐RD) process for isobutyl acetate synthesis is proposed. The steady‐state and dynamic characteristics of the PST‐RD process are evaluated based on Aspen and Aspen Dynamic. Steady‐state optimization results show that the energy consumption and the total annual cost (TAC) reduced by 42.32% and 34.20% compared with the conventional two‐column process, respectively. Subsequently, two control structures of the PST‐RD process under a rigorous model are developed and evaluated by large disturbances in throughput and feed composition. Dynamic simulation results show that peak dynamic transients can be effectively reduced by adding a Q/F feedforward control structure. Furthermore, the effective heat integration of high‐pressure (HP) and low‐pressure (LP) columns can be realized by implementing composition/pressure cascade control when the capacity of the LP column increases.
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 | 0.001 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".