Investigating the Influence of Rheological Parameters on Mechanical Performance of 3D-printed Lattice Structures Using Doehlert Design

Lattice structures are composed of repeating unit cells arranged in a three-dimensional pattern. They usually exhibit higher stiffness and strength compared to conventional designs, making them ideal for lightweight, high-performance applications. Due to their complex geometry, they are often impossible to manufacture with traditional methods, positioning Additive Manufacturing (AM) as the preferred solution. While these structures are typically manufactured using rigid materials, flexible materials are gaining interest due to their enhanced damping properties under compression. When manufactured through processes such as Fused Deposition Modelling (FDM), the rheological behaviour of the material during printing plays a critical role in determining the mechanical properties of the final structure. Challenges such as poor adhesion, can induce anisotropy and affect the failure mechanisms of these structures. During extrusion, variations in shear rate and temperature significantly impact the material's performance, making control over parameters like viscosity and shear rates essential. This study aims to optimize the rheological properties of printable materials to enhance the mechanical performance of lattice structures using a Doehlert design of experiments strategy. A challenging flexible lightweight lattice structure, made from Thermoplastic Polyurethane (TPU), is chosen to be mechanically improved for a morphing wing application. Flow curves of the molten material are obtained across different temperatures, and the time-temperature superposition principle is applied to obtain the exact rheological conditions used in the study. By integrating a Response Surface Methodology (RSM) with a Doehlert design, the extrusion parameters – specifically viscosity and shear rates – are fine-tuned to achieve optimal mechanical properties. This approach demonstrates that high-performance lattice structures can be efficiently produced with minimal experimentation, overcoming traditional trial-and-error methods commonly used in the field.