Multi-Objective Optimisation of Biodiesel Synthesis in Simulated Moving Bed Reactor

In this work, multi-objective optimisation study was performed to determine the performance improvement in a simulated moving bed reactor (SMBR) for biodiesel synthesis. The selection of the operating parameters such as switching time, liquid flow rates in various sections, as well as the length and number of columns is not straightforward in an SMBR. In most cases, conflicting requirements and constraints influence the optimal selection of the decision (operating or design) variables. A mathematical model that predicts single-column experimental results well was modified and verified experimentally for multiple-column SMBR system. In this article, a few multi-objective optimisation problems were carried out for both existing set-up as well as at the design stage. A non-dominated sorting genetic algorithm (NSGA) was used as the optimisation tool for the optimisation study. Due to conflicting effect of process parameters, the multi-objective optimisation study resulted in non-dominated Pareto optimal solutions. It was shown that significant increase in yield and purity of biodiesel in SMBR was possible both for operating and at design stage.

Automated summary

A multi-objective optimization study was conducted in a simulated moving bed reactor (SMBR) for biodiesel synthesis, leading to significant improvements in yield and purity. The mathematical model used in the study was modified and experimentally verified for multiple-column SMBR system, showing promise for optimizing both existing setups and designs.