  The optimal design seeks the best possible solution(s) for a mechanical
structure, device, or system, satisfying a series of requirements and leading
to the best performance. In this work, optimized nozzle shapes have been
designed for a wide range of polymer melts to be used in extrusion-based
additive manufacturing, which aims to minimize pressure drop and allow greater
flow control at large extrusion velocities. This is achieved with a twofold
approach, combining a global optimization algorithm with computational fluid
dynamics for optimizing a contraction geometry for viscoelastic fluids and
validating these geometries experimentally. In the optimization process,
variable coordinates for the nozzle's contraction section are defined, the
objective function is selected, and the optimization algorithm is guided within
manufacturing constraints. Comparisons of flow-type and streamline plots reveal
that the nozzle shape significantly influences flow patterns. Depending on the
rheological properties, the optimized solution either promotes shear or
extensional flow, enhancing the material flow rate. Finally, experimental
validation of the nozzle performance assessed the actual printing flow, the
extrusion force and the overall print control. It is shown that optimizing the
nozzle can significantly reduce backflow-related pressure drop, positively
impacting total pressure drop (up to 41%) and reducing backflow effects. This
work has real-world implications for the additive manufacturing industry,
offering opportunities for increased printing speeds, enhanced productivity,
and improved printing quality and reliability. Our research contributes to
advancing extrusion-based printing processes technology, addressing industry
demands and enhancing the field of additive manufacturing.
