The 9th International Conference on Multiscale Materials Modeling

Presentation information

Symposium

M. Time- and History-Dependent Material Properties

[SY-M2] Symposium M-2

Mon. Oct 29, 2018 3:45 PM - 5:45 PM Room4

Chair: Emanuela Zaccarelli(University of Rome I, Italy)

[SY-M2] MMM in aircraft industries: use cases for simulation of additive manufacturing

Annett Seide1, Thomas Goehler1, Roman Sowa2 (1.MTU Aero Engines AG, Germany, 2.MTU Aero Engines Polska Sp. z o. o., Poland)

MTU Aero Engines is Germany's leading engine manufacturer and an established global player in the industry. Computational Materials Engineering and Additive Manufacturing (AM) of high temperature alloys are only two of the forward-looking techniques MTU is working with. To represent industrial application of MMM it will be displayed how MTU uses Materials Simulation techniques for AM process.

For a materials engineer some of the key aspects of the AM process are texture, microstructure (e.g. precipitate size and phase fraction) and mechanical properties (e.g. yield stress). Consequentially, the AM simulation includes laser/electron beam scanning strategy, interaction of beam and powder, microstructure evolution and crystal plasticity.

AM simulation at MTU covers amongst others the following typical use cases: (1) description of the influence of chemical composition on microstructure and mechanical properties, (2) determination of surface roughness depending on scanning strategy and (3) heat treatment optimization with regard to yield strength and texture. All of those show the strong coupling between material/manufacturing history and resulting material properties.
The main focus will be on the use case regarding determination of surface roughness as a function of scanning strategy. The goal will be to present requirements and methods related to the specific use case as well as an insight into the industrial application itself. We will give one example of successful integration of materials modeling and simulation as tools to tailor materials properties through process parameter optimization.