Conference Agenda

This study examines the microstructural and mechanical behavior of composite specimens comprising 3D-printed concrete and ordinary mortar. CT-based pore analysis was carried out for the printing, mortar, and bonding regions, and the low-order probability function was applied to quantify pore distribution and continuity. Directional tensile strength and stiffness were further evaluated using a phase-field fracture model. The printing region showed an anisotropic pore network with relatively low continuity parallel to the layer stacking, while the mortar region displayed isotropic characteristics. The bonding region exhibited an intermediate pore distribution but was notably affected by continuous pores oriented perpendicular to the stacking direction, leading to reduced interfacial bonding strength. Overall, the findings highlight how interfacial morphology governs the mechanical response of printed–mortar composite systems.

Additive Manufacturing (AM) methods like Fused Deposition Modelling (FDM) in 3D printing present the opportunity to construct geometrically complex polymeric reinforcements for cementitious composites. However, FDM 3D printed material can be highly anisotropic such that printing path-dependent models using the Lattice Beam Model (LBM) have been developed. These explicitly model the inter-layer and intralayer bonds that exist in FDM 3D printed reinforcements by assigning experimentally obtained interface properties that significantly differ from the bulk material. To illustrate the aforementioned methodology, it is used to numerically investigate particularly complex types of FDM 3D printed reinforcement for cementitious composites subjected to bending. These have a Poisson’s ratio that is tailored in accordance with the stress-strain distribution, such that their cross-sections change over the height of the beams. Three Tailored Poisson’s Ratioreinforcement (TPR) designs are modelled considering printing path-dependent anisotropy as a result of the FDM 3D printing technique. Subsequently, preliminary simulations of these reinforcements submerged in cementitious matrix to form a composite are discussed. The lattice models show that incorporating the anisotropy present in FDM 3D printed reinforcement is important, because simulations assuming isotropic properties result in significant overestimation in strength and completely change the fracture behaviour.

3D concrete printing (3DCP) brings automation to construction, reduces material usage, increases design flexibility, and eliminates the need for formwork. However, it is a complex process governed by numerous interdependent parameters that are often tuned through trial-and-error. This can lead to unforeseen failures during printing, such as instability or plastic collapse of the material. Computational modeling offers a means to predict and prevent such failures by enabling virtual design assessment, process optimization, and evaluation of how variations during printing influence the final structure. The structural failure during printing is primarily governed by the material response of fresh concrete, making the choice of constitutive model critical. Plasticity-based models are commonly employed to assess buildability, yet most approaches neglect the nonlinear behaviour observed experimentally for fresh concrete before failure. This simplification often leads to underestimation of deformations and overprediction of structural stability. In this work, a numerical framework is developed to investigate how nonlinear isotropic hardening influences the failure behaviour of printed structures. The model is based on a von Mises plasticity formulation with a saturation-type hardening law and is implemented in an updated Lagrangian finite element framework with the Jaumann stress rate to capture geometric nonlinearity. The printing process is simulated through a pseudodensity-based layer activation method, while time-dependent material parameters are incorporated to account for structural buildup and aging. A systematic parameter study is performed on printed cylinders with varying diameters and hardening parameters to investigate how geometry and material hardening jointly influence buildability. The results show that the number of printed layers before failure depends strongly on the hardening rate, particularly for slender, instability-prone geometries, while stable configurations are largely unaffected.

A lack of reliable predictive models for early-age behaviour is impeding the widespread adoption of 3D concrete printing (3DCP), a new construction technique that is gaining popularity. The layer-by-layer deposition method presents special difficulties regarding changing mechanical characteristics, heat effects, and moisture loss. In this work, the time-dependent response of printed concrete is simulated using a Multiphysics Finite Element Model (MFEM) framework. By connecting the development of shrinkage and strains with the progression of hydration, the model integrates mechanical behaviour with hygro-thermal-chemical (HTC) analysis. This model that has been calibrated against published calorimetry data is used to capture the kinetics of hydration. Eigenstrains are used to model important early-age processes, such as drying shrinkage, autogenous shrinkage and total shrinkage. The framework facilitates process parameter optimisation and provides predictive insights into early-age behaviour. Experimental validation and extension to long-term durability modelling will be part of future research.

Mixing time is a critical parameter in printcrete (3D printed concrete), directly influencing mixture homogeneity and printability, which in turn govern construction efficiency and overall cost. This study proposes a computational framework for determining the optimal mixing time based on a non-contact monitoring system. The homogeneity was quantitatively characterized by analyzing surface texture images, from which a texture index was computed as the standard deviation of grayscale values to evaluate degree of homogeneity. Simultaneously, printability was assessed via rheological properties, with key parameters derived through a linear calibration model linking mixer torque to offline rheometric data. By integrating target thresholds for both homogeneity and rheological performance, the optimal mixing time was identified using a non-contact monitoring system. The proposed method was applied to a printcrete mixture incorporating a polycarboxylate ether superplasticizer and an aluminum sulfate-based accelerator. Results demonstrate that the approach reliably determines stage-specific mixing times, ensuring consistent printability and mechanical performance.