Study links rheology and kinematics for more precise prediction of 3D printing processes

The quality of additive manufacturing processes largely depends on the interaction between material properties and motion sequences during deposition. A recent scientific study now shows how this interaction can be described more accurately using numerical models. The study presents an approach that directly couples rheological material parameters with deposition kinematics, enabling a well-founded prediction of material behavior in 3D printing.

At the core of the work is the use of Computational Fluid Dynamics to simulate material flow during the printing process in detail. Especially for pasty, polymeric, or bio-based materials, viscosity, shear thinning, and yield stress influence the shape stability of deposited strands. Using CFD models, these effects can for the first time be systematically correlated with printing speed, nozzle diameter, and the motion profile of the print head. This makes it possible to deliberately optimize deposition patterns and reduce typical defects such as uneven layer thicknesses or material accumulation.

The results were published in the scientific journal Physics of Fluids and were produced as part of a collaboration between Ghent University and An-Najah National University. The study was led by Simon Kerckhove, who worked under the supervision of Francisco Gilabert, Flavio Marchesini, and Bahaa Shaqour. Experimental validations were carried out in the laboratories of An-Najah National University and supported by students, underscoring the practical relevance of the research.

For industrial and medical applications, the approach is particularly relevant, as reproducible component quality and process stability are key requirements. The study shows that a model-based design of printing parameters can help shorten development times and use materials more efficiently. In this way, the work provides another building block for the increasing level of process control in 3D printing.

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