Aeroelastic Optimization of an Industrial Compressor Rotor Blade Geometry

TitleAeroelastic Optimization of an Industrial Compressor Rotor Blade Geometry
Publication TypeConference Paper
Year of Publication2018
AuthorsVanti F, Pinelli L, Arnone A, Schneider A, Astrua P, Puppo E
Conference NameASME Turbo Expo 2018: Turbine Technical Conference and Exposition
VolumeVolume 2D: Turbomachinery
Paginationpp. V02DT46A016; 10 pages
Conference LocationOslo, Norway
ISBN Number978-0-7918-5102-9
Accession NumberWOS:000456493900016
Other NumbersScopus 2-s2.0-85054060103

This paper describes a multidisciplinary optimization procedure applied to a compressor blade-row. The numerical procedure takes into account both aerodynamic (efficiency) and aeromechanic (flutter free design) goals nowadays required by turbomachinery industries and is applied to a low pressure compressor rotor geometry provided by Ansaldo Energia S.p.A.. Some typical geometrical parameters have been selected and modified during the automatic optimization process in order to generate an optimum geometry with an improved efficiency and, at the same time, a safety flutter margin. This new automatic optimization procedure, which now includes a flutter stability assessment, is an extension of an existing aerodynamic optimization process, which randomly perturbs a starting 3D blade geometry inside a constrained range of values, build the fluid mesh and run the CFD steady analysis. The new implementation provides the self-building of the solid mesh, the FEM analysis and finally the unsteady uncoupled aeroelastic analysis to assess the flutter occurrence. After simulating a wide range of geometries, a database with all the constraint parameters and objective functions is obtained and then used to train a neural network algorithm (ANN). Once the ANN validation error is converged, an optimization strategy is used to build the Pareto front and to provide a set of optimum geometries redesigning the original compressor rotor. The aim of this paper is to show the opportunity to take into account the aeroelastic issues in optimization processes, thus satisfying both aerodynamic and aeromechanic requirements.


paper GT2018-76474