Session: 22-05 Aeroelastic Instabilities and Mistuning

Paper Number: 125093

125093 - Manufacturing and Build Variations Modelling for Multi-Stage Axial Compressors: Forced Response Predictions 

The trend of modern multi-stage axial compressors for gas turbine applications is towards less conservative designs in the pursuit of higher efficiency. To avoid potential aero-mechanical issues, the development and validation of computationally efficient and accurate numerical tools is of paramount importance. This paper demonstrates how highly automated forced response analyses are integrated in the design of a new multi-stage axial compressor for industrial gas turbine applications. In case of twin-shaft applications with wide operating range requirements, each concept can require hundreds of analyses. The capability to perform rapid design iterations considering aero-mechanical stability, unlocks new regions of the design space, with potential issues being identified and rectified at an early stage in the product development process.  Moreover, the scope of the assessments can be extended to consider effects which would not traditionally be considered as part of the design process, such as mistuning. The methodology is here applied to in-tolerance geometrical variations, modelling the associated uncertainty on forced response. Characterizing the sensitivity to mistuning provides actionable data for the development of robust design concepts. The methodology used for the design of a new compressor and subsequent predictions are validated against tip timing data from a full-scale engine test, demonstrating the accuracy of both the analyses and design process.

Presenting Author: Giuseppe Bruni Siemens Energy

Presenting Author Biography: Giuseppe Bruni is currently employed as a Principal Aerodynamicist by Siemens Energy Industrial Turbomachinery Ltd, Lincoln, UK, where he has been working since 2016. He received the BSc and MSc degrees in Mechanical Engineering from University of Padova, Italy, respectively in 2014 and 2016. He received the MSc in Gas Turbine Technology from Cranfield University, UK in 2016, and is currently working towards a PhD at the University of Lincoln, UK, on the topic of Machine learning modelling of manufacturing variations on compressor aerodynamic
performance. His research interest include the aerodynamic, aero-mechanical analysis and design of axial compressors, as well as development and applications of optimisation and machine learning methods. He is a Chartered Engineer and member of the IMechE.

Authors:

Giuseppe Bruni Siemens Energy
Senthil K. Krishnababu Siemens Energy Industrial Turbomachinery Ltd.
Simon Jackson Siemens Energy Industrial Turbomachinery Ltd.