Optimization of methanol synthesis reactor using genetic algorithms [An article from: Chemical Engineering Journal]

This digital document is a journal article from Chemical Engineering Journal, published by Elsevier in 2005. The article is delivered in HTML format and is available in your Amazon.com Media Library immediately after purchase. You can view it with any web browser.

Description:
This paper presents a study on optimization of methanol synthesis reactor to enhance overall production. A mathematical heterogeneous model of the reactor was used for optimization of reactor performance, both at steady state and dynamic conditions. Here, genetic algorithms were used as powerful methods for optimization of complex problems. Initially, optimal temperature profile along the reactor was studied. Then, a stepwise approach was followed to get an optimal two-stage cooling shell to maximize production rate. These optimization problems were performed through steady-state optimizations with regard to dynamic properties of the process. The optimal reactor with two-stage cooling shell presented higher performances. This optimization approach enhanced a 2.9% additional yield throughout 4 years, as catalyst lifetime. Therefore, we can deduce to redesign methanol synthesis reactor with a two-stage cooling shell reactor based on this study.