Speaker
Description
Additive Manufacturing in Construction (AMC) offers a unique advantage by combining automation with customization. Moreover, AMC introduces an innovative design approach, adding material only where it is structurally or functionally necessary. This makes AMC both cost-effective and resource-efficient. However, 3D printing with concrete presents specific challenges related to buildability. The deposited strands must support not only their own weight but also the weight of the layers above. Additionally, during the construction of concrete structures via 3D printing, issues such as elastic buckling and plastic deformation can lead to structural failure. Therefore, numerical modelling of the deposition process, considering process parameters, is crucial for predicting structural stability, optimizing the printing process, and minimizing trial-and-error experimentation.
This contribution outlines the framework and numerical implementation of a path- and process-based finite element approach to simulate the structural build-up during deposition. The modelling approach establishes a direct coupling between process parameters and simulation, accounting for the time-dependent material behaviour of fresh concrete. Various numerical examples related to the optimization of process parameters are presented to demonstrate the functionality of the approach. These studies analyse the convergence and numerical stability of the implementation concerning the sensitivity of time-dependent material properties as well as time and spatial discretisation. Additionally, explicit examples are used to apply the proposed approach for conducting parametric studies that investigate the buildability of printed structures through the optimization of process parameters.
