Motivation
We specialize in developing advanced computational models for laser-based additive manufacturing, with a particular focus on Laser Powder Bed Fusion (LPBF) and Laser Directed Energy Deposition (L-DED) processes. Our work bridges multiple scales—from microscopic laser-powder interactions to component-level property predictions—enabling precise control and optimization of manufacturing processes for complex hybrid and porous structures.
Research Areas
Microscale Simulation (1-100 μm)
Capturing fundamental physics at the particle and grain level:
- Laser-material interaction: Energy absorption, reflection, and heat distribution in individual powder particles (20-100 μm)
- Powder dynamics: Particle kinematics, melting behavior, and deposition characteristics
- Phase transformations: Solid-liquid-gas transitions under extreme cooling rates (>10⁶ K/s)
- Melt pool physics: Fluid dynamics, surface tension, and microscale solidification
- Microstructure evolution: Grain formation during rapid solidification
Mesoscale Simulation (100 μm – 10 mm)
Efficient modeling of features and multi-track interactions:
- Track interactions: Adjacent and overlapping laser pass behavior
- Layer dynamics: Thermal history and inter-layer bonding
- Porosity modeling: Representative volume elements (RVEs) for porous substrates
- Feature geometry: Single webs, multiple tracks, and local structural elements
- Thermo-mechanical coupling: Temperature evolution and residual stress development
Macroscale Simulation (> 10 mm)
Component-level predictions through virtual manufacturing:
- Property distribution: Spatial and temporal mapping of material characteristics
- Global residual stress: Component-wide stress states from complete build sequences
- Path optimization: Impact analysis of scan pattern strategies
- Material gradients: Modeling spatially varying compositions and porosity
- Process planning: Virtual representation of complete fabrication workflows
Computational Methods & Tools
JuliaAM: In-House Finite Differences (FDM) based Simulation Framework
Our custom-built Julia-based FDM platform designed for high-performance additive manufacturing simulations:
- GPU acceleration: Native Julia capabilities for massively parallel computing
- Multiphysics coupling: Integrated thermal, mechanical, and fluid dynamics solvers
- Modular architecture: Flexible integration of physical models and numerical schemes
- High Performance Computing and optimization: Efficient distributed computing on cluster systems
Complementary Tools
- CFD-DEM coupling: Integrated computational fluid dynamics and discrete element methods
- OpenFoam solvers: Detailed thermo-fluid structure simulations
- Custom FDM implementations: GPU-parallelized finite difference solvers
Applications
Our simulation capabilities enable:
- Process optimization for novel materials and complex geometries
- Virtual defect prediction and prevention strategies
- Residual stress management for enhanced component performance
- Data-driven manufacturing parameter selection
- Integration with real-time process monitoring and control
Funding
![[Translate to English:] DFG](/fileadmin/cpe/Forschung/Soft_Robots/Bilder/dfg_logo_schriftzug_blau_foerderung_de.jpg "Druck"){kind=logo}
Multifunctional High-Performance Components made of hybrid porous materials
Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – Project-ID 511263698 – TRR 375