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Turbomachinery design by a swarm-based optimization method coupled with a CFD solver

  • Ampellio, Enrico (Department of Mechanical and Aerospace Engineering, Politecnico di Torino) ;
  • Bertini, Francesco (GE Avio S.r.l.) ;
  • Ferrero, Andrea (Department of Mechanical and Aerospace Engineering, Politecnico di Torino) ;
  • Larocca, Francesco (Department of Mechanical and Aerospace Engineering, Politecnico di Torino) ;
  • Vassio, Luca (Department of Electronics and Telecommunications, Politecnico di Torino)
  • Received : 2015.07.02
  • Accepted : 2015.09.24
  • Published : 2016.04.25
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Abstract

Multi-Disciplinary Optimization (MDO) is widely used to handle the advanced design in several engineering applications. Such applications are commonly simulation-based, in order to capture the physics of the phenomena under study. This framework demands fast optimization algorithms as well as trustworthy numerical analyses, and a synergic integration between the two is required to obtain an efficient design process. In order to meet these needs, an adaptive Computational Fluid Dynamics (CFD) solver and a fast optimization algorithm have been developed and combined by the authors. The CFD solver is based on a high-order discontinuous Galerkin discretization while the optimization algorithm is a high-performance version of the Artificial Bee Colony method. In this work, they are used to address a typical aero-mechanical problem encountered in turbomachinery design. Interesting achievements in the considered test case are illustrated, highlighting the potential applicability of the proposed approach to other engineering problems.

Keywords

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