Additive Fertigung
Filtern
Erscheinungsjahr
- 2022 (5) (entfernen)
Dokumenttyp
- Vortrag (4)
- Zeitschriftenartikel (1)
Schlagworte
- Additive Fertigung (2)
- Korrosion (2)
- Trinkwasser (2)
- Early-age concrete (1)
- Hygiene (1)
- Hygienische Bewertung (1)
- Lithium aluminosilicates (1)
- Model calibration (1)
- Ontology (1)
- Optimization workflow (1)
Organisationseinheit der BAM
- 7 Bauwerkssicherheit (5) (entfernen)
Eingeladener Vortrag
- nein (4)
Concrete has a long history in the construction industry and is currently one of the most widely used building materials. Especially precast concrete elements are frequently utilized in construction projects for standardized applications, increasing the quality of the composite material, as well as reducing the required building time. Despite the accumulated knowledge, continuous research and development in this field is essential due to the complexity of the composite combined with the ever-growing number of applications and requirements. Especially in view of global climate change, design aspects as CO2 emissions and resource efficiency require new mix designs and optimization strategies. A result of the material’s high complexity and heterogeneity on multiple scales is that utilizing the full potential with changing demands is highly challenging, even for the established industry. We propose a framework based on an ontology, which automatically combines experimental data with numerical simulations. This not only simplifies experimental knowledge transfer, but allows the model calibration and the resulting simulation predictions to be reproducible and interpretable. This research shows a way towards a more performance oriented material design. Within this talk we present our workflow for an automated simulation of a precast element, demonstrating the interaction of the ontology and the finite element simulation. We show the automatic calibration of our early-age concrete model [1, 2], to improve the prediction of the optimal time for the removal of the form work.
Hydrous lithium aluminosilicate (L–A–S–H) and lithium aluminate (L–A–H) gels are candidate precursors for glass-ceramics and ceramics with potential advantages over conventional processing routes. However, their structure before calcination remained largely unknown, despite the importance of precursor structure on the properties of the resulting materials. In the present study, it is demonstrated that L–A–S–H and L–A–H gels with Li/Al ≤ 1 can be produced via an organic steric entrapment route, while higher Li/Al ratios lead to crystallization of gibbsite or nordstrandite. The composition and the structure of the gels was studied by thermogravimetric analysis, X-ray diffraction, 27Al and 29Si magic-angle spinning nuclear magnetic resonance, and Raman spectroscopy. Aluminium was found to be almost exclusively in six-fold coordination in both the L–A–H and the L–A–S–H gels. Silicon in the L–A–S–H gels was mainly in Q4 sites and to a lesser extent in Q3 sites (four-fold coordination with no Si–O–Al bonds). The results thus indicate that silica-rich and aluminium-rich domains formed in these gels.
Numerical simulations are essential in predicting the behavior of systems in many engineering fields and industrial sectors. The development of accurate virtual representations of actual physical products or processes (also known as digital twins) allows huge savings in cost and resources. In fact, digital twins would allow reducing the number of real, physical prototypes, tests, and experiments, thus also increasing the sustainability of production processes and products’ lifetime. Standard numerical methods fail in providing real time simulations, especially for complex processes such as additive manufacturing applications.
This work aims to use a reduced order model for efficient wire arc additive manufacturing simulations, calibrations and real-time process control. Model reduction, e.g. the proper generalized decomposition [1,2] method, is a popular concept to decrease the computational effort. A new mapping approach [3] was applied to simulate a moving heat source with the proper generalized decomposition. Using this procedure even complex models can be simulated in real-time. The physical model is later on calibrated with the use of a stochastic model updating process and the reduced order model, leading to an optimized real-time simulation.
In this contribution, a proper generalized decomposition model for a bead-on-plate wire arc additive manufacturing is presented. It is also coupled with a stochastic model updating process identifying the heat source characteristics as well as the boundary conditions of the transient thermal problem, whereas the heat source shape is simulated using a Goldak heat source
Elektrochemische Messungen zur hygienischen Bewertung additiv gefertigter Bauteile werden diskutiert. Die Bewertung und Details des Werkstoffs werden beschrieben, Anwendungsbeispiele gezeigt.