Optimal design of liquid-solid circulating fluidized bed for continuous protein recovery

Jahirul Mazumder, Jingxu Zhu, Ajay K. Ray

Research output: Journal PublicationArticlepeer-review

16 Citations (Scopus)


In recent years, liquid-solid circulating fluidized beds (LSCFBs) are being applied as a reactor system in a number of new applications. This study addresses optimal design of LSCFB system at the design stage for the continuous protein recovery. The operation of LSCFB system for continuous protein recovery is associated with several important objectives such as production rate and recovery of protein as well as the amount of ion exchange resin requirements, all of which need to be optimized simultaneously. In this study, an experimentally validated mathematical model was used to perform the multi-objective optimization of the LSCFB system at the design stage. In the optimization study, eight operating and design parameters were used as decision variables. These variables were chosen based on systematic sensitivity analysis of the system which showed complex interplay of the decision variables over the system performance indicators. Elitist non-dominated sorting genetic algorithm with its jumping gene adaptation (NSGA-II-aJG) was used to solve a number of two- and three-objective function optimization problems. The optimization resulted in Pareto optimal solutions, which provides a broad range of non-dominated solutions due to conflicting behavior of the decision variables on the system performance indicators. Compared to the optimization results obtained in the operating stage, the performance of the system was further improved at the design stage optimization as changes in physical dimensions of the LSCFB system can provide better performance than would have been possible by adjusting only the operating parameters.

Original languageEnglish
Pages (from-to)32-47
Number of pages16
JournalPowder Technology
Issue number1
Publication statusPublished - 10 Apr 2010
Externally publishedYes


  • Circulating fluidized bed
  • Design
  • Genetic algorithm
  • Multi-objective optimization
  • Pareto set
  • Protein recovery

ASJC Scopus subject areas

  • General Chemical Engineering


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