Abstract
Secondary flow features of turbine blade flows are only assessable by 3D computational fluid dynamics (CFD) which is a time-consuming task. In this paper a fast automatic optimization process for the aerodynamic improvement of three-dimensional turbine blades is described and applied to a two-stage turbine rig. Basically, standard tools are used where the 3D CFD analysis, however, is significantly accelerated by a novel CFD solver running on graphics processing units (GPU) and the entire blade is parameterized in 3D. This approach shows that three-dimensional optimization of turbine blades is feasible within days of runtime and finds an improved blade design.
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References
Arabnia M, Ghaly W (2009) A strategy for multi-point shape optimization of turbine stage in three-dimensional flow. In: Proceedings of ASME turbo expo 2009, GT2009-59708, Orlando, Florida
Brandvik T, Pullan G (2011) An accelerated 3D Navier-Stokes solver for flows in turbomachines. J Turbomach 133(2):021025
Briasco G, Cravero C, Macelloni P (2010) Turbine blade profile optimization using soft-computing techniques. In: Proceedings of 2nd international conference on engineering optimization, Lisbon, Portugal
Dennis B, Egorov I, Han ZX, Dulikravich G, Poloni, C (2000) Multi-objective optimization of turbomachinery cascades for minimum loss, maximum loading, and maximum gap-to-chord ratio. In: Proceedings of 8th AIAA/NASA/USAF/ISSMO symposium on multidisciplinary analysis and optimization, AIAA 2000-4876, Long Beach, California
Ghaly W (2010) Shape representation. In: North Atlantic treaty organization, research & technology organization (ed) strategies for optimization and automated design of gas turbine engines, RTO-EN-AVT-167
Giannakoglou KC (1999) Designing turbomachinery blades using evolutionary methods. In: Proceedings of 44th ASME gas turbine & aeroengine congress, 9-GT-181, Indianapolis
Gräsel J, Keskin A, Swoboda M, Przewozny H, Saxer A (2004) A full parametric model for turbomachinery blade design and optimisation. In: Proceedings of ASME DETC 2004, DETC2004-57467, Salt Lake City, Utah
Hansen N, Ostermeier A (2001) Completely derandomized self-adaptation in evolution strategies. Evol Comput 9(2):159–195
Hasenjäger M, Sendhoff B, Sonoda T, Arima T (2005) Three dimensional aerodynamic optimization for an ultra-low aspect ratio transonic turbine stator blade. In: Proceedings of ASME turbo expo 2005, GT2005-68680, Reno-Tahoe, Nevada
Keskin A, Haselbach F, Meyer M, Janke E, Brandvik T, Pullan G (2011) Aerodynamic design and optimzation of turbomachinery component using a GPU flow solver. In: Proceedings of 9th European conference on turbomachinery fluid dynamics and thermodynamics, Istanbul, Turkey
Menzel S, Olhofer M, Sendhoff B (2006) Evolution design optimisation of a turbine stator blade using free form deformation techniques. In: Proceedings of conference on modelling fluid flow (CMFF’06), Budapest, Hungary
Nagel MG (2004) Numerische Optimierung dreidimensional parametrisierter Turbinenschaufeln mit umfangsunsymmetrischen Plattformen—Entwicklung, Anwendung und Validierung. PhD thesis, Universität der Bundeswehr München
Pierret S, Van den Braembussche RA (1999) Turbomachinery blade design using a navier-stokes solver and artificial neural network. J Turbomach 121(2):326–332
Pierret S, Demeulenaere A, Gouverneur B, Van den Braembussche RA (2000) Designing turbomachinery blades with the function approximation concept and the navier-stokes equations. In: Proceedings of 8th AIAA/USAF/NASA/ISSMO symposium on multidisciplinary analysis and optimization, AIAA 2000-4879, Long Beach, California
Shahpar S, Lapworth L (2003) Padram parametric design and rapid meshing system for turbomachinery optimisation. In: Proceedings of ASME turbo expo 2003, GT2003-38698, Atlanta, Georgia, pp 579–590
Acknowledgments
This work has been carried out in collaboration with Rolls-Royce Deutschland as part of the research project VIT 3 (Virtual Turbomachinery, contract no. 80142272) funded by the State of Brandenburg, the European Community and Rolls-Royce Deutschland. Rolls-Royce Deutschland’s permission to publish this work is greatly acknowledged.
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Amtsfeld, P., Bestle, D., Meyer, M. (2015). Direct 3D Aerodynamic Optimization of Turbine Blades with GPU-Accelerated CFD. In: Greiner, D., Galván, B., Périaux, J., Gauger, N., Giannakoglou, K., Winter, G. (eds) Advances in Evolutionary and Deterministic Methods for Design, Optimization and Control in Engineering and Sciences. Computational Methods in Applied Sciences, vol 36. Springer, Cham. https://doi.org/10.1007/978-3-319-11541-2_12
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DOI: https://doi.org/10.1007/978-3-319-11541-2_12
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