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Optimization and probabilistic analysis of structures optimized for topology and smoothly varying material orientations
Publikationstyp
Conference Presentation
Date Issued
2023-06-06
Sprache
English
Citation
15th World Congress on Structural and Multidisciplinary Optimization (WCSMO 2023)
Contribution to Conference
Modern robot-based additive manufacturing (AM) setups enable material deposition on curved surfaces in contrast to conventional flat printing planes. This has been applied to 3D printing of carbon fiber reinforced plastic (CFRP) parts. To align the printing paths with the optimal fiber orientation, principal stress directions can be used to derive the curved planes. This method fails to provide optimal printed material orientations in the presence of multiple load cases.
The current work presents an approach for simultaneous topology and material orientation optimization. The method is designed to deliver material layouts optimized for multiple load cases as well as being well suited for the following AM process, specifically the generation of curved printing layers and continuous tool paths.
Additionally, the optimized structures are analyzed for robustness with respect to the scatter of material orientations. The mean and standard deviation of their compliance are determined using the Monte Carlo method as well as efficient Taylor-based methods. The probabilistic analyses allow for applying Robust Design Optimization (RDO) methods to the simultaneous topology and material orientation optimization to reduce loss of performance due to the interpretation of the optimized material layout for the printing process.
The current work presents an approach for simultaneous topology and material orientation optimization. The method is designed to deliver material layouts optimized for multiple load cases as well as being well suited for the following AM process, specifically the generation of curved printing layers and continuous tool paths.
Additionally, the optimized structures are analyzed for robustness with respect to the scatter of material orientations. The mean and standard deviation of their compliance are determined using the Monte Carlo method as well as efficient Taylor-based methods. The probabilistic analyses allow for applying Robust Design Optimization (RDO) methods to the simultaneous topology and material orientation optimization to reduce loss of performance due to the interpretation of the optimized material layout for the printing process.
DDC Class
624: Civil Engineering, Environmental Engineering