A modified particle swarm optimization algorithm for the design of a double-pad aerostatic bearing with a pocketed orifice-type restrictor

S. H. Chang, Yeau-Ren Jeng

Research output: Contribution to journalArticlepeer-review

18 Citations (Scopus)

Abstract

The performance of an aerostatic bearing with a pocketed orifice-type restrictor is affected by the bearing size, pocket size, orifice design, supply pressure, and bearing load. This study proposes a modified particle swarm optimization (MPSO) algorithm to optimize a double-pad aerostatic bearing. In bearing optimization, the upper and lower bearing designs are independent and several design variables that affect bearing performance must be considered. This study also applies the concept of mutation from a genetic algorithm. The results show that the MPSO algorithm has a global search capability and high efficiency to optimize a problem with several design variables and that the mutation can provide an avenue for particles to escape from a local optimal value.

Original languageEnglish
Article number021701
JournalJournal of Tribology
Volume136
Issue number2
DOIs
Publication statusPublished - 2014 Jan 1

All Science Journal Classification (ASJC) codes

  • Mechanics of Materials
  • Mechanical Engineering
  • Surfaces and Interfaces
  • Surfaces, Coatings and Films

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