Research Projects

The project aims to gain a fundamental understanding of Shotcrete 3D Printing (SC3DP) technology in order to produce sustainable, multi-objective optimised reinforced concrete components with precise surface quality and improved building physics through functional integration. The project aims to minimise the carbon footprint of 3D-printed structures by exploring various material strategies, such as reducing the cement content by increasing the aggregate size or replacing cement with another binder, as well as design methods to optimise concrete use in order to reduce the overall volume of concrete used. In addition, the project focuses on establishing reliable material and process control, with an emphasis on new material laws for printability and durability, real-time monitoring of concrete properties, and component build-up strategies.

https://amc-trr277.de/projects/project-area-a/focus-area-project-a04/

This project investigates various additive manufacturing processes for manufacturing strategies for integrating fibre reinforcements. Therefore, a range of novel processing techniques must be developed and tested with regard to structural feasibility and design options for selected components. Conceptually, all possible strategies are subsumed under the basic process of winding a flexible fibre reinforcement strand with a digitally controlled robot arm. The prefabrication of the reinforcement is part of this manufacturing scenario in order to achieve a continuous process chain and improve existing concrete 3D printing.

https://amc-trr277.de/projects/project-area-a/focus-area-project-a05/

While traditional construction processes are characterised by fragmentation of construction knowledge, new digital tools enable the integration of all project participants early on in the project phases. This requires a bidirectional flow of information into a central building information model. The aim of this project is to investigate the bidirectional relationship between production and planning at the scale levels of component manufacturing (using computer vision and machine learning to improve manufacturing), on-site component assembly (including the use of mixed reality) and on an industrial scale (e.g. integrated project management).

https://amc-trr277.de/projects/project-area-c/focus-area-c-06/