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In dieser Arbeit wurde eine Methode entwickelt, um Informationen über Defektverteilungen aus CT-Analysen von Gussbauteilen (AlSiMg,EN-AC- 43000) auf ein Finite-Elemente-Modell (FE) zu übertragen. Da die Daten einer CT-Analyse sehr groß sind, war eine Datenreduktion erforderlich. Dies erfolgte durch die am Fraunhofer IWM entwickelte Software MaterialDatatFusion MDF, bei dem die Porenverteilung vereinfacht wird. Die Porenverteilungen wurden untersucht und auf die FE-Modelle gemappt. Daneben wurde ein Deformations- und Versagensmodell für den Aluminiumguss mit Einfluss des Defektanteils kalibriert. Damit und mit der elementweisen ermittelten Verteilung der Porosität wurden Probenversuche simuliert, die aus realen Gussbauteilen entnommen wurden. Für die exakte Probenentnahme diente MDF der genauen Zuordnung der Porosität im Prüfbereich. Die simulierten Kraft-Verschiebungskurven sowie die ermittelte Porosität wurden mit der realen Verteilung der Poren und den Experimenten verglichen.
A digital twin of an automotive component was created by fusing space-resolved data. The benefit of fused data from different virtual and experimental sources like CAD, FEM, DIC, IR and laser scanners is demonstrated with a recyclable car-seat back-shell and its mechanical impact testing. Component properties depend on its shape, its material conditions and its manufacturing process. Along the whole product life cycle nowadays a huge amount of data accrues. The aim is the use of this information to improve products and save resources. To understand the mechanics of materials in use and forecast components' behavior in simulations, the MaterialDataFusion (MDF) tool was created. MDF correlates information geometrically and in time to one file of fused data. Within the virtual geometry of a component, all available data are registered in a common coordinate system with local accuracy. MDF is able to correlate all data on a common grid. The grid can be created within the tool by using standard shells or solids Finite Element (FE) meshes. The local FE size can be adjusted dependent on the spatial resolution of the data. Across all scales, data on different levels brought together. To use the accumulated information for the parametrization or validation of material models, the correlation process also can be performed using predefined meshes from usual FE pre-processors imported in MDF. These meshes are used within the correlation as an information carrier. The correlated information grid is than exported as a data frame, which contains the local available static or time dependent information on each node. One can include porosity, fiber orientation, heat treatment history, microstructure information, deformation and heat development in mechanical tests and all other data measured or simulated on components. As an example, along the life cycle of a recyclable car-seat back-shell, consisting of basalt fibers laminates and molded polylactic acid (PLA), different data from multiple institutions where fused in MDF and used to validate a complex hybrid material model. Whereat, the demonstrated analyses on the correlated back-shell data file are just a small inside into the possibilities of digital twins, created by MDF.