Improving the reliability and efficiency of a multi-hull vacuum evaporator
Bibliographic record
Abstract
The scope of application of multi-vessel vacuum evaporator units for concentrating solutions and their prospects for implementation in the dairy, starch and molasses and other industries for thickening a product with high viscosity, production of dried dairy products, canned milk with sugar, as well as in conditions of low cost of steam when burning local fuels or in the combined production of electricity and heat are determined. An improved methodology for calculating a multi-vessel vacuum evaporator with steam compression for condensing dairy products is proposed, the feature of which is the cellular structure of the calculation model in the form of calculation tables formed according to individual technological and design parameters of the unit. The results of the modernization of a four-hull vacuum evaporator with steam compression from Alfa Laval Schaeffers, performed on the basis of the analysis of data from its long-term operation for the concentration of dairy products and calculation, experimental and commissioning studies in order to improve the main functional units to ensure reliable and efficient operation, are presented. The effectiveness of the implemented technical solutions has been confirmed by the results of commissioning tests of the modernized plant and during its further operation. The scientific and technical experience of PJSC "Kalynivka Machine-Building Plant" (Kalynivka, Vinnytsia region) in modernization and commissioning of the above four-hulled unit, together with the experience in production of highly efficient single-hulled vacuum evaporators with mechanical compression ВВУ-Мк and double-hulled evaporators with combined compression ВВУ-Мк-Пк, is the basis for organization of production of multi-hulled evaporators with steam compression in Ukraine.
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 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".