Improving centrifugal compressor performance by optimizing the design of impellers using genetic algorithm and computational fluid dynamics methods

Mohammad Omidi, Shu Jie Liu, Soheil Mohtaram, Hui Tian Lu, Hong Chao Zhang

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

It has always been important to study the development and improvement of the design of turbomachines, owing to the numerous uses of turbomachines and their high energy consumption. Accordingly, optimizing turbomachine performance is crucial for sustainable development. The design of impellers significantly affects the performance of centrifugal compressors. Numerous models and design methods proposed for this subject area, however, old and based on the 1D scheme. The present article developed a hybrid optimization model based on genetic algorithms (GA) and a 3D simulation of compressors to examine the certain parameters such as blade angle at leading and trailing edges and the starting point of splitter blades. New impeller design is proposed to optimize the base compressor. The contribution of this paper includes the automatic creation of generations for achieving the optimal design and designing splitter blades using a novel method. The present study concludes with presenting a new, more efficient, and stable design.

Original languageEnglish
Article number5409
JournalSustainability (Switzerland)
Volume11
Issue number19
DOIs
StatePublished - Oct 1 2019

Keywords

  • Centrifugal compressor
  • Computational fluid dynamics (CFD)
  • Genetic algorithm (GA)
  • Optimization

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