The integrity of structural and functional components is particularly crucial in space travel – both during launch and in orbit. Based on extensive material, process and analysis expertise, Fraunhofer IKTS supports and advises on the development of new materials and products, the determination of characteristic values, the clarification of complex failure mechanisms and the achievement of legal and quality standards. In addition to all the necessary standard analysis methods, special, in some cases globally unique, testing options are available.
We also develop high-precision non-destructive testing methods (NDT) and systems for structural health monitoring (SHM) – essential for quality assurance and service life monitoring of aerospace components. The technologies enable the early detection of defects, material fatigue and structural changes – without damaging components.
Material testing under extreme conditions
- High-temperature tests up to 1600°C (air, vacuum)
- Hot gas corrosion testing of materials and components (up to 1500 °C, 40 m/s to 100 m/s, natural gas, H2 and natural gas/H2 mixtures, water vapour content in the fuel gas 12 % to 30 %)
- Ceramic high-temperature probe heads for flow measurement technology
- Thermomechanical in-situ analyses, e.g. for additively manufactured or hierarchical structures
- Electrical, thermal and mechanical fatigue tests
- Fractography and failure analysis (e.g. using SEM, TEM, µ and nano X-ray microscopy, in-situ microscopy for structural behavior under load)
- Design and testing of components based on the actual thermal, mechanical and chemical loads during the mission
- Long-term reliability tests to evaluate service life (> 25 years), including media resistance
Simulation, digital technologies and AI
- Material characterization for precise material models in the simulation (e.g. to describe ageing or fatigue)
- Augmented reality for real-time visualization of complex 3D data in the inspection of aerospace components
- AI and machine learning for the automated evaluation of NDT data (e.g. for CFRP components)
- Machine learning-based prediction models for failure probabilities
- Digital twins for real-time monitoring and condition assessment of space systems
- DICONDE standards and data fusion (e.g. HF eddy current method) for structured data utilization in space travel