Abstract Computer Numerical Control (CNC)-knitted textiles are flexible, lightweight, and highly customisable, which makes them promising materials for architectural and construction applications. In the context of tensile structures, both the final shape and the mechanical properties of knitted textiles can be controlled to follow a specific design intent. However, predicting their mechanical behaviour is challenging and currently requires experience, domain-specific knowledge, and extensive prototyping. Developing a computational method to design bespoke knitted textiles for a target geometry and behaviour is therefore essential. The proof-of-concept workflow introduced in this paper uses the Force Density Method (FDM) combined with gradient-based optimisation to compute force density distributions for a target geometry abstracted as a mesh. These force densities are discretised into domains and mapped to knit architectures with distinct deformation capacities, resulting in functionally graded textiles. The workflow is tested on a non-symmetric target geometry and evaluated through physical prototyping. The results highlight both the potential of the approach and the need for refined force density–knit architecture mapping and alternatives to prototyping. This computational method paves the way for material-informed form-finding, which can facilitate the integration of CNC-knitted textiles into architectural applications, such as flexible formwork.
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Nikoletta Christidi
Delft University of Technology
Christian Louter
Mariana Popescu
Massachusetts Institute of Technology
Architectural Intelligence
Massachusetts Institute of Technology
Delft University of Technology
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Christidi et al. (Mon,) studied this question.
synapsesocial.com/papers/6966e70113bf7a6f02bff32a — DOI: https://doi.org/10.1007/s44223-025-00111-5