Another central research focus of the group is the physics-based interpretation of ELO data (Electron Optical Data) for the precise characterization of the electron beam in powder bed–based electron beam melting. Accurate knowledge of the beam profile, power density distribution, and focal position is essential for understanding energy deposition and forms the foundation for reliable process simulations and reproducible manufacturing strategies.
At the core of this work are raytracing-based models that reproduce the electron beam along the entire electron-optical system, from the cathode assembly to the powder bed surface. Building on these models, methods are developed to reconstruct the actual beam profile from experimentally accessible ELO measurements. This makes it possible not only to determine effective beam diameters, but also to capture complex intensity distributions, aberrations, and process-relevant deviations from idealized Gaussian beam profiles.
These activities make a substantial contribution to the quantitative linkage between machine parameters, beam physics, and the resulting melt behavior. The insights gained are directly integrated into numerical process models, enabling a far more realistic description of local energy deposition than is achievable using simplified beam assumptions.
Research on ELO data interpretation was largely driven within the framework of the Collaborative Research Center SFB 814 “Additive Manufacturing” and today forms a key pillar for subsequent projects. In particular, within the ERC project AMELI, the developed raytracing and reconstruction approaches provide the basis for a consistent, physics-based description of the electron beam process—from electron optics to the resulting microstructure.
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Publications:
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Processing Strategies for Electron Beam Based Powder Bed Fusion
In: Dietmar Drummer, Michael Schmidt (ed.): Progress in Powder Based Additive Manufacturing, Springer Nature, 2025, p. 127-148 (Springer Tracts in Additive Manufacturing, Vol.Part F386)
DOI: 10.1007/978-3-031-78350-0_7 - , , , , :
Extracting powder bed features via electron optical images during electron beam powder bed fusion
In: Additive Manufacturing Letters 10 (2024), Article No.: 100220
ISSN: 2772-3690
DOI: 10.1016/j.addlet.2024.100220 - , , , , , :
In-situ electron beam characterization for electron beam powder bed fusion
In: Additive Manufacturing 96 (2024), Article No.: 104567
ISSN: 2214-7810
DOI: 10.1016/j.addma.2024.104567 - , , :
In situ build surface topography determination in electron beam powder bed fusion
In: Progress in Additive Manufacturing (2024)
ISSN: 2363-9512
DOI: 10.1007/s40964-024-00621-0 - , , , , , , , , , :
Evaluation of Additively-Manufactured Internal Geometrical Features Using X-ray-Computed Tomography
In: Journal of Manufacturing and Materials Processing (2023)
ISSN: 2504-4494
DOI: 10.3390/jmmp7030095 - , , , :
A Ray Tracing Model for Electron Optical Imaging in Electron Beam Powder Bed Fusion
In: Journal of Manufacturing and Materials Processing 7 (2023), Article No.: 87
ISSN: 2504-4494
DOI: 10.3390/jmmp7030087 - , , , :
Surface topographies from electron optical images in electron beam powder bed fusion for process monitoring and control
In: Additive Manufacturing 60 (2022), Article No.: 103172
ISSN: 2214-7810
DOI: 10.1016/j.addma.2022.103172