STREAMS HEAT INTEGRATION IN THE SEPARATION PROCESS OF THE FURFURAL-WATER HETEROAZEOTROPIC MIXTURE BY USING TWO STRETCHING COLUMNS
Bibliographic record
Abstract
The process of azeotropic mixtures rectification takes place in many branches of the chemical industry. This process requires significant energy consumption both for heating and evaporation of process streams, and for vapor condensation and cooling of products. The consumption of external energy essentially depends on the methods of separation processes organization. Pinch analysis is one of the modern methods for designing chemical-technological systems with the aim of optimal use of external energy sources by maximizing the heat integration of system process streams, taking into account the limitations of a particular manufacture, the requirements of environmental safety and environmental protection. In this paper the heat integration of the heteroazeotropic furfural-water mixture separation process by two columns was considered. In each column the azeoptrope is a light-boiling one, and one of the mixture components is a low-boiling one. The heat and material balances of the rectifying plant were calculated and the table of its streams was formed, that is, the data of the chemical-technological system were extracted. From the total set of heat streams, the subset was selected for heat integration. Composite curves for the selected heat streams subject to heat integration were built and their relative position on the temperature-enthalpy diagram was analyzed. This analysis showed that for a certain value of the minimum temperature difference in the heat exchange equipment Тmin, there is a threshold problem. The problem was formulated for a value of Тmin slightly less than the threshold value that led to a slight increase in the consumption of external energy carriers. Options for further improvement of the network of heat exchangers were considered, and the occurrence of a cycle through the pseudopinch was identified. It gave possibility to remove a heat exchanger with a low load and redistribute this load among to other ones. Restoring Тmin in this case is impossible, because a strict restriction on the absence of hot utilities is accepted. Significant savings in external utilities load have been demonstrated. For retrofit modern Alfa Laval heat exchange equipment was selected for all the necessary positions.
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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 | 0.000 |
| 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) | 0.001 | 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".