Optimizing aggregate content and size distribution in low-carbon 3D-printed concrete via DEM simulation

To mitigate the reduced extrudability typically associated with low-carbon concrete formulations of 3D-printed concrete, this study focuses on optimizing aggregate content and size distribution through discrete element method (DEM) simulations.A two-phase soft shell–hard core DEM model was employed, in which aggregates were represented as rigid cores surrounded by concentric soft shells corresponding to cement paste, allowing explicit representation of particle-scale interactions during extrusion. The effects of binder-to-aggregate ratios ranging from 0.4 to 1.0 and aggregate fineness moduli between 2.5 and 3.3 on extrusion pressure, filament morphology, and clogging behavior were systematically evaluated. The results indicate that binder-to-aggregate ratios below 0.6 caused a sharp increase in extrusion pressure and frequent nozzle clogging, whereas a ratio of 0.8 ensured stable and continuous extrusion. In addition, finer aggregates with a fineness modulus of 2.5 reduced filament width variation to below 10%, indicating improved flow uniformity and geometric consistency. An optimal extrusion performance was achieved through the combination of a binder-to-aggregate ratio of 0.8 and a fineness modulus of 2.5, balancing material sustainability and printability. This study establishes a computational framework for the design of low-carbon 3D-printed concrete through aggregate tailoring, enabling a reduction in cement usage without compromising extrusion performance.