Reduced order modelling for turbomachinery shape design. Issue 2 (7th February 2020)

• Record Type: Journal Article
• Authors: Ferrero, Andrea; Iollo, Angelo; Larocca, Francesco
• Is Part Of: International journal of computational fluid dynamics. Volume 34:Issue 2(2020)
• Page Start: 127
• Page End: 138
• Publication Date: 2020-02-07
• Subjects: Reduce order modelling -- POD -- turbomachinery -- shape optimisation -- discontinuous Galerkin -- RANS; Fluid dynamics -- Data processing -- Periodicals; 532.05
• DOI: 10.1080/10618562.2019.1691722
• Languages: English
• ISSNs: 1061-8562

Abstract

ABSTRACT: Reduced order modelling (ROM) techniques allow to reduce the cost of shape optimisation problems. In the present work, the compressible turbulent flow around a gas turbine profile is studied by a Discontinuous Galerkin (DG) scheme. The simulations are accelerated by the combination of two existing ROM approaches: Domain Decomposition and Local Proper Orthogonal Decomposition in a DG (LPOD-DG) framework. In particular, the focus is fixed on the aerofoil suction side which is deformed while the pressure side remains fixed. The proposed method allows to reduce significantly the number of degrees of freedom in the simulation. The method is evaluated by performing a set of random predictions for shapes not included in the training database and comparing the obtained results with high-fidelity simulations. The approach is also compared to a p-adaptive scheme. Finally, the use of an automatic adaptive technique is investigated in order to improve the prediction accuracy at runtime.