Kinder einbeziehen

Oberbichler, Katharina

doi:10.33196/pm202204024001

Cited by 1 publication

(1 citation statement)

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“…Geometry Form-Finding The geometry of the fabric formwork was form-found with EQlib (Oberbichler, 2019) by prestressing a membrane between the elements of the structure. This configuration creates a prestressed gridshell (Cao et al, 2021) that carries the load of the unhardened concrete.…”

Section: Computational Form-findingmentioning

confidence: 99%

Robotic knitcrete: computational design and fabrication of a pedestrian bridge using robotic shotcrete on a 3D-Knitted formwork

Rennen,

Gantner,

Dielemans

et al. 2023

Front. Built Environ.

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The research project presented here aims to develop a design-informed manufacturing process for complex concrete shell structures in additive manufacturing and thus overcome limitations of traditional construction methods such as formwork- and labor intensity. To achieve this, an effort was made to merge the two technologies of CNC knitted stay-in-place formwork, known as KnitCrete, and robotically applied shotcrete, known as Shotcrete 3D Printing (SC3DP), and thereby reduce their respective limitations. The proposed workflow unites both digital fabrication methods into a seamless process that additionally integrates computational form finding, robotically applied fiber reinforcement, CNC post processing and geometric quality verification to ensure precision and efficiency. As part of a cross-university, research-based teaching format, this concept was implemented in the construction of a full-scale pedestrian bridge, which served as a demonstrator to evaluate the capabilities and limitations of the process. While overcoming some challenges during the process, the successful prove of concept shows a significant leap in digital fabrication of complex concrete geometry, reducing reliance on labor-intensive methods. The results shown in this paper make this fabrication approach a promising starting point for further developments in additive manufacturing in the construction sector.

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Section: Computational Form-findingmentioning

confidence: 99%