Structural considerations in zeotropic distillation sequences with multiple feeds

Autor: José A. Caballero, Juan Javaloyes-Antón, Juan A. Labarta
Přispěvatelé: Universidad de Alicante. Departamento de Ingeniería Química, Universidad de Alicante. Instituto Universitario de Ingeniería de los Procesos Químicos, Computer Optimization of Chemical Engineering Processes and Technologies (CONCEPT)
Rok vydání: 2021
Předmět:
Zdroj: RUA. Repositorio Institucional de la Universidad de Alicante
Universidad de Alicante (UA)
Popis: The separation of multiple feed streams with some common components using sequences of distillation columns produces a rich space of alternatives that must be considered. In this work, we present the main structural characteristics of sequences generated when we want to take advantage of the synergies of common components in multiple feed streams to reduce both, energy consumption and the total number of distillation columns. In general, the sequence of separation tasks of the whole system can be obtained from the sequences of separation tasks of each one of the feeds. However, the integration in actual columns is not so straightforward and we must consider aspects like the optimal location of feeds in multiple-feed columns; and the alternatives of integration of common sub-mixtures (when possible) in actual columns. Besides, the optimal sequence of separation tasks for each feed is not necessarily the same when all of them are considered simultaneously. We show that the minimum number of actual columns, without considering further intensification, depends on the number of components in each feed and on the possibilities of integration of common sub-mixtures, so we extend the concepts of regular and basic column sequences to deal with these new situations. The examples show the potential savings in energy and number of columns compared to maintain isolated each feed; mixing the feed streams or an incorrect integration. The authors acknowledge financial support to the “Generalitat Valenciana” under project PROMETEO 2020/064.
Databáze: OpenAIRE