Topology optimization offers a possibility to derive load-compliant structures. These structures tend to be complex, and conventional manufacturing offers only limited possibilities for their production. Additive manufacturing provides a remedy due to its high design freedom. However, this type of manufacturing can cause areas of different material properties in the final part. For example, in selective laser melting, three areas of different porosity can occur depending on the process parameters, the geometry of the part and the print direction, resulting in a direct interrelation between manufacturing and design. In order to address this interrelation in design finding, this contribution presents an optimization method in which the three porous areas are identified and the associated material properties are considered iteratively in a topology optimization. For this purpose, the topology optimization is interrupted in each iteration. Afterwards, the three areas as well as the material properties are determined and transferred back to the topology optimization, whereby those properties are used for the calculation of the next iteration. By using the optimization method, a design with increased volume-specific stiffness compared to a design of a standard topology optimization can be created and will be used in the future as a basis for the extension by a global strength constraint to maintain the maximum permissible stress and the minimum wall thickness.
Inhalt Die steigende Komplexität von technischen Systemen ist bei der Entwicklung neuer Produkte eine große Herausforderung. Zur Unterstützung des Produktentwicklers bei der Bewältigung dieser Herausforderung werden computergestützte Methoden eingesetzt, um frühzeitig das Produktverhalten abschätzen zu können. Dabei ist der Einsatz von CAE-Methoden einzelner Domänen nicht ausreichend, um Wechselwirkungen zwischen bspw. der Elektrotechnik und dem Maschinenbau abzubilden. Daher bedarf es einer Kopplung von Simulationsmethoden, die die verschiedenen Domänen miteinander verknüpft. Mit dem dadurch bedingten erhöhten Modellierungsaufwand gehen jedoch Entwicklungsrisiken einher, die bewertet werden müssen. Mithilfe des vorgestellten Modellierungsansatzes wird diese Bewertung des Entwicklungsrisikos gekoppelter CAE-Methoden beherrschbar gemacht, wodurch eine strategische Planung der Entwicklungsaktivitäten ermöglicht wird.
In the laser powder bed fusion process (PBF-LB), components are built up incrementally by locally melting metal powder with a laser beam. This process leads to inhomogeneous material properties of the manufactured components. By integrating these specific material properties into a topology optimization algorithm, product developers can be supported in the early phases of the product development process, such as design finding. For this purpose, a topology optimization method was developed, which takes the inhomogeneous material properties of components fabricated in the PBF-LB process into account. The complex pore architecture in PBF-LB components was studied with micro-computed tomography (µCT). Thereby, three characteristic regions of different porosity were identified and analyzed. The effective stiffness in each of these regions was determined by means of resonant ultrasonic spectroscopy (RUS) as well as finite element analysis. Afterward, the effective stiffness is iteratively considered in the developed topology optimization method. The resulting design proposals of two optimization cases were analyzed and compared to design proposals derived from a standard topology optimization. To evaluate the developed topology optimization method, the derived design proposals were additionally manufactured in the PBF-LB process, and the characteristic pore architecture was analyzed by means of µCT.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.