Abstract
3D concrete printing technology (3DCP) have gained wide attention. They indicated their potential to become a serious supplement to conventional concrete casting in molds. The main reason for this is it directly addresses the challenges related to the sustainability and productivity of the construction industry. However, the current practice is based on the trial-and-error procedure, which makes the research of the 3DCP process expensive and time-consuming. One of the reasons is that there exist significant knowledge gaps regarding the relations between the design, material, and process parameters. Therefore, it is of vital importance to establish a relation between the process parameters and the printed product to avoid unreliability and failure. By implementing a numerical simulation of the 3DCP process, a more fundamental understanding of the relations between the printing process, the process parameters, and the properties of the printed product could be achieved.
In this study, layer-wise Finite Element Method (FEM) combined with a pseudodensity approach, known from in topology optimization is applied. Along with the progressing printing process, all material parameters vary spatially and temporarily due to the time dependency of the curing process. The numerical simulations allow to reliably estimate the failure mechanisms that might occur during the 3D concrete printing of a wall structure.
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Acknowledgment
The work has been financially supported by different institutions which is highly acknowledged. Among them are: DAAD (Ethiopian - German Exchange of PhD candidates), DFG (German Research Foundation) priority program 1886 “Polymorphic uncertainty modelling for the numerical design of structures” and the Federal State of Thuringia, Germany.
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Mengesha, M., Schmidt, A., Göbel, L., Lahmer, T. (2023). Numerical Modeling of 3D Concrete Printing Wall Structure to Reliably Estimate the Failure Mechanisms. In: Rossi, P., Tailhan, JL. (eds) Numerical Modeling Strategies for Sustainable Concrete Structures. SSCS 2022. RILEM Bookseries, vol 38. Springer, Cham. https://doi.org/10.1007/978-3-031-07746-3_24
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