Session: 26-02 Applications using Probabilistic and Machine Learning Methods

Paper Number: 124232

124232 - Influence of Shape and Size of Casting Defects on the LCF Performance of MAR-M247 – A Path Towards a Probabilistic Model 

Jan Radners¹, Christoph Schweizer¹, Michael Schlesinger¹, Stefan Eckmann¹,
Malek Al-Ameri², Christian Amann², Peter Gumbsch^1,3, Kai Kadau⁴

¹ Fraunhofer IWM, Freiburg, Germany

² Siemens Energy Global GmbH & Co. KG, Mülheim a. d. R., Germany

³ Karlsruhe Institute of Technology (KIT), Institute for Applied Materials, Karlsruhe, Germany

⁴ Siemens Energy Inc., Charlotte, NC

 

Gas turbines represent a way to fill supply gaps of renewable energy sources and help manage peak loads. With the expansion of renewable energy sources, the demand for more flexible operating conditions for gas turbines is increasing. As a result, the number of startup and shutdown cycles - the low cycle fatigue (LCF) loading of a gas turbine component - increases substantially. This work investigates the LCF performance of a common rotor blade material to support the future transition toward more flexible power plant operation. One of the goals of this multi-year government-funded project is the development of a probabilistic life model of cast material, including defects such as porosity.

This work investigates the influence of casting defects on the LCF performance of cast MAR-M247 at realistic engine conditions (i.e., temperature and stress). The work is based on results presented at the ASME Turbo Expo 2023 (GT2023-101940). This work focuses on an in-depth investigation of the defect influence, while the experimental database is significantly extended.

Specimens extracted from large turbine blades were cycled at 850 °C under strain-controlled LCF conditions at a strain ratio of R=-1. Different sizes and shapes of defects are investigated on the fracture surfaces of tested specimens. The defects are parametrized using various descriptive parameters. The individual impact of these parameters on the LCF performance of the material is analyzed and compared to each other.

Furthermore, the influence of the varying microstructure at the location of the porosity is studied. These uncertainties lead to significant variations in the resulting life cycles. The integration of substantial parameters into a probabilistic concept is discussed.

Presenting Author: Jan Radners Fraunhofer Institute for Mechanics of Materials IWM

Presenting Author Biography: www.linkedin.com/in/jan-radners

Authors:

Jan Radners Fraunhofer Institute for Mechanics of Materials IWM
Christoph Schweizer Fraunhofer Institute for Mechanics of Materials IWM
Michael Schlesinger Fraunhofer Institute for Mechanics of Materials IWM
Stefan Eckmann Fraunhofer Institute for Mechanics of Materials IWM
Malek Al-Ameri Siemens Energy Global GmbH & Co. KG
Christian Amann Siemens Energy Global GmbH & Co. KG
Peter Gumbsch Fraunhofer Institute for Mechanics of Materials IWM and Karlsruhe Institute of Technology (KIT), Institute for Applied Materials
Kai Kadau Siemens Energy Inc.