Optimal design of extractive distillation for acetic acid dehydration with N-methyl acetamide

作     者：You, Xinqiang Gu, Jinglian Peng, Changjun Rodriguez-Donis, Ivonne Liu, Honglai 

作者机构：East China Univ Sci & Technol State Key Lab Chem Engn Shanghai 200237 Peoples R China East China Univ Sci & Technol Dept Chem Shanghai 200237 Peoples R China Chongqing Univ Sch Chem & Chem Engn Chongqing 400044 Peoples R China Univ Toulouse INRA ENSIACET INPT Lab Chim Agroind Toulouse France 

出 版 物：《CHEMICAL ENGINEERING AND PROCESSING-PROCESS INTENSIFICATION》 (化学工程和加工技术)

年 卷 期：2017年第120卷

页      面：301-316页

核心收录：

学科分类：0820[工学-石油与天然气工程] 0817[工学-化学工程与技术] 08[工学] 

基　　金：Doctoral Fund of Ministry of Education of China [2016M601528] National Natural Science Foundation of China [21606026, 21276073] 

主　　题：Acetic acid dehydration Extractive distillation Sequential quadratic programming Multi-objective optimization Genetic algorithm 

摘      要：A distinctive strategy for entrainer recycling is proposed in this work for acetic acid (AA) dehydration by extractive distillation by using N methyl acetamide (NMA). The use of standard entrainers such as DMF or DMSO has the main drawback of forming an azeotrope with acetic acid. However, the vapour liquid equilibrium AA NMA exhibits a tangential pinch point at NMA end composition. The new strategy rises from the thermodynamic analysis of the ternary diagram that which involves no azeotrope. As a result, acetic acid with high purity can be obtained by the recycling of the entrainer with a relaxed constraint in its purity. Optimization studies are discussed by using two approaches: two-step optimization method with Sequential Quadratic Programming (TSOM case) and the multi-objective genetic algorithm. The multi-objective genetic algorithm allowed the computation of the optimal acetic acid dehydration with an impurity of 3% in the recycled entrainer. Significant cost savings are achieved thanks to the optimization of both columns together. Energy consumption is reduced by 12.8% and 56.9% whereas TAC is saved by 28.4% and 56.3% compared with optimal case TSOM (impurity content 1%) and a published Case Ref (impurity content 0.01%), respectively.