Abstract
During service life of an aircraft engine, highly loaded compressor blades are subject to wear and may get damaged. In order to prevent further damage, blades are refurbished and partial defects are removed by blend repairs. Although the blending of the blade only leads to small shape modifications, it impacts the structural properties significantly. Even a slight variation of the geometry may cause a significant change in the modal behavior. Therefore, it has to be analyzed how blend repairs affect the vibrations of the refurbished blade and how the repair processes can be improved. In the present work, the optimal shape of blend repairs is determined. The first objective function is supposed to be the related quantity of material removed. The second objective of the optimization results from the tuning of the blade’s eigenfrequencies. The location, form, and orientation of the blend is determinable by a parameterizable repair model serving as input for a multi-objective Particle Swarm Optimization algorithm. Studies are carried out aiming at establishing an efficient optimization procedure for the blend repair of integral bladed compressor disks. In particular, the study assesses and presents the influence of the blend repair parameters on the decisive eigenfrequencies related to material removal.
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Notes
- 1.
In the following, it is implied that x and v are vectors comprising as many elements as the dimension of the optimization problem.
- 2.
In other words, this condition means that particles with at least one smaller objective function value have a chance of \(\alpha \) to become the personal best particle.
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Acknowledgements
The support of the German Research Foundation (DFG, Deutsche Forschungsgemeinschaft) through its Collaborative Research Centre (SFB, Sonderforschungsbereich) 871 is gratefully acknowledged.
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Berger, R., Häfele, J., Hofmeister, B., Rolfes, R. (2018). Blend Repair Shape Optimization for Damaged Compressor Blisks. In: Schumacher, A., Vietor, T., Fiebig, S., Bletzinger, KU., Maute, K. (eds) Advances in Structural and Multidisciplinary Optimization. WCSMO 2017. Springer, Cham. https://doi.org/10.1007/978-3-319-67988-4_122
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DOI: https://doi.org/10.1007/978-3-319-67988-4_122
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