Optimization of a New Integrated Separation Process for Azeotropes Based on Genetic Programming

A solution strategy of a distillation‐membrane separation process based on genetic programming algorithm (GP) is proposed. It can automatically match diverse membrane materials according to different azeotropic systems and generate various integrated processes. For the membrane, which is still in th...

Full description

Saved in:
Bibliographic Details
Published in:Chemical engineering & technology Vol. 44; no. 12; pp. 2355 - 2364
Main Authors: Wang, Xiao-Hong, Ding, Xin, Du, Peng, Tian, Zeng-Hu, Chen, Jing-Xuan
Format: Journal Article
Language:English
Published: Frankfurt Wiley Subscription Services, Inc 01.12.2021
Subjects:
ISSN:0930-7516, 1521-4125
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:A solution strategy of a distillation‐membrane separation process based on genetic programming algorithm (GP) is proposed. It can automatically match diverse membrane materials according to different azeotropic systems and generate various integrated processes. For the membrane, which is still in the experimental research stage, a theoretical prediction method of membrane cost is recommended. Taking the benzene‐cyclohexane system as an example, a GO‐AgNPs/PI membrane and polyurethane membrane were matched, respectively, and the optimal integrated processes can be obtained. The GP strategy provides a strong guidance for the comprehensive design and optimization of distillation‐membrane separation by using various new membranes. A comprehensive solution strategy based on the genetic programming algorithm is established, which is applied to quickly design and study an integrated process of distillation‐membrane separation with the benzene‐cyclohexane azeotropic system as an example. Various membrane materials can be matched automatically according to different azeotropic systems and generate various integrated processes.
Bibliography:ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
ISSN:0930-7516
1521-4125
DOI:10.1002/ceat.202100352