Modelling orthotropic behaviour in robotic 3D printing of cementitious matrices with natural fibres and metallic reinforcement: a digital twin approach

Robotic 3D printing with cementitious materials is reshaping construction by enabling geometrically complex and resource-efficient structures. Yet, the lack of robust analytical frameworks for validating the print quality and behaviours of fibre-reinforced composites continues to constrain the broader use of this technology in the construction industry. This study proposes a digital twin (DT)-based methodology for the post-production assessment of cementitious elements reinforced with natural and metallic fibres. By comparing photogrammetric point clouds of printed components to their original toolpath-derived meshes, one implements a geometry-based DT workflow that captures deviations, anisotropy, and layer-wise inconsistencies between layers that occur during fabrication. This process enables the qualitative and quantitative evaluation of geometric conformance and deformation. It provides critical insights into how reinforcement strategies affect material deposition, layer morphology, and build stability. The digital analyses highlight the influence of fibre content, reinforcement type, and rheological behaviour on the orthotropic performance of 3D printed elements. The core contribution lies in demonstrating how DT tools rooted in geometric fidelity and mesh-to-cloud comparisons can inform adaptive design, improve quality control, and support the development of performance-based standards for additive manufacturing in architecture and construction. This research advocates the integration of DT feedback loops into the 3D concrete printing pipeline, reinforcing the role of digital verification in advancing reliable and sustainable construction technologies.