Computational materials engineering
Computational Materials Engineering
The materials simulation group at MTU uses various computational approaches to achieve three main goals:
- understand the role of local material chemistries on mechanical properties
- reduce experimental testing by identifying suitable parameters
- analyze the thermo-kinetic potential of alloy specifications to optimize performance and productibility
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Application examples
- Optimizing alloy composition to minimize cost without compromising on performance
- Calculating optimal heat treatment parameters for a new alloy or process
- Finding optimum process conditions for new braze compositions
- Prediction of static mechanical properties (e.g. Rp0.2, creep life, Young’s modulus)
- Materials and processes benchmarking
Software solutions
We work within astrong research network and have optimised and enhanced a number of commerciallyavailable software solutions. For instance, we have created new databases, linked different softwares and added tailored applications to better model and simulate the micromechanical evolution of the most commonturbine materials used today.
We use the key software solutions:
- MatCalc
- ThermoCalc
- Micress
- SAMPLE2D
- Calculix
- Abaqus
