Design optimization for fir-tree root of turbine blade considering manufacturing variations

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

An optimization design system for fir-tree root of turbine blade has been developed in this paper. In the system, a parametric model of the blade and rim was established based on the parametric design language APDL, and nonlinear contact method was used for analysis by ANSYS, meanwhile some optimization algorithms, such as Pattern Search Algorithm, Genetic Algorithm, Simulated Annealing Algorithm and Particle Swarm Optimization, were adopted to control the optimizing process. Five cases of manufacturing variation in contact surfaces between root and rim were taken into account, and the design objective was to minimize the maximum equivalent stress of root-rim by optimizing eight critical geometrical dimensions of the root and rim. As a result, the maximum equivalent stress of root-rim decreases markedly after the optimization in all cases. In consideration of both precision and computing time, particle swarm optimization is assessed as the best algorithm to solve structure optimization problem in this work. Corresponding to five different cases of manufacturing variation, the maximum equivalent stress of root and rim reduces by 7%, 8%; 27%, 24%; 27%, 22%; 25%, 19%; 10%, 14% using the Particle Swarm Optimization.

Original languageEnglish
Title of host publicationManufacturing Process and Equipment
Pages2733-2737
Number of pages5
DOIs
StatePublished - 2013
Event4th International Conference on Manufacturing Science and Engineering, ICMSE 2013 - Dalian, China
Duration: 30 Mar 201331 Mar 2013

Publication series

NameAdvanced Materials Research
Volume694 697
ISSN (Print)1022-6680

Conference

Conference4th International Conference on Manufacturing Science and Engineering, ICMSE 2013
Country/TerritoryChina
CityDalian
Period30/03/1331/03/13

Keywords

  • Fir-tree root and rim
  • Manufacturing variations
  • Optimization algorithm pattern
  • Structure optimization

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