3D‐Printed Concrete Footbridges (2023-09)¶

Digital fabrication with concrete (DFC) is fast becoming an attractive alternative for components (i.e., façades, urban furniture) and structural typologies (i.e., short-span footbridges, columns, floor systems) for which complex geometries derived from particular aesthetical criteria and/or construction time constrictions are governing parameters. Additionally, some authors claim that this process allows improving the sustainability of structures, as less material is necessary compared to traditional concrete solutions, thus reducing greenhouse gas emissions linked to material consumption. Nonetheless, the environmental implications of DFC are still under scrutiny and remain objectively unquantified. In this study, a sustainability assessment model to allow decision-makers to evaluate and compare concrete footbridge alternatives—from the sustainability perspective—including those constructed by means of 3D printed concrete (3DPC) techniques, is presented. The proposed approach is based on the MIVES method. For this purpose, the most representative criteria and indicators of sustainability identified are measured and weighted-aggregated in a decision-making tree. The sustainability index (SI) of each alternative is the outcome derived from the application of the model, and the SI was used as reference for evaluating the alternatives. The sustainability of 3Dprinted footbridges is quantified and compared to other concrete-based solutions: traditional reinforced cast-in-place and precast concrete, as traditional solutions, and ultra-high performance precast concrete and textile-reinforced concrete, as innovative alternatives. The results of the analysis lead to conclude that 3D-printed footbridges have positive impacts on environmental and social indicators, but economic indicators still need to be improved to attain a competitive solution. The approach proposed herein to assess the sustainability of footbridges can be extended to other cases and stakeholders' preferences by adapting the components of the method to sensitivities and particular boundary conditions of other scenarios.