Modeling of Material Jetting Additive Manufacturing with Applications to Paper Machine Fabrics

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Hume, Chad A.
Rosen, David W.
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Material jetting-based (MJ) additive manufacturing (AM) is a promising manufacturing technology uniquely suited to enable new innovation, especially at the mesoscale, like novel paper machine press fabrics. The objective of this research is to improve the understanding of mesoscale feature fabrication via material jetting AM and improve our understanding of how to model the material jetting fabrication process. Additionally, we seek expand the state of the art for paper machine press fabrics through the design and analysis of novel membrane layers. To begin, a series of benchmark test specimens with parametrically varying mesoscale features were designed and fabricated using an industry leading material jetting machine. These specimens were characterized to explore the printing fidelity with respect to minimum manufacturable feature size, dimensional accuracy, and shape accuracy, as well as any respective dependencies on design variables (i.e., feature shape, size, orientation, and thickness). Geometric deformations affecting the feature accuracy as well as shape accuracy were revealed to be of significant degree. While the ultimate impact on any proposed design would depend on the application, the presented methods can be leveraged to define DfAM guidelines and provide clarity on expected feature outcome. Next, high-fidelity multiphase droplet models are developed to explore how deposition dynamics affect feature formation. What makes this work novel is the exploration of deposition on non-uniform surfaces near a layer edge. Results showed that local deposition dynamics will result in material flow beyond the layer boundary, which will expand the layer boundary, reducing deposition height and lead to feature deformation. Additionally, the developed models were used to simulate multiple droplet deposition and coalescence, as would be seen during the printing process, to form a multi-line, 3-layer feature. In doing so, the material overflow was observed to form the edge rounding seen during physical characterization. By better understanding this effect process control improvements can be made to improve feature resolution and fidelity, and a preliminary example showing an extra edge pass was demonstrated. A novel Quasi-static Boundary-based method for rapidly modeling the material jetting process was developed and demonstrated. The key assumption of this approach is that for the material properties and timescales of interest for the MJ process, with a reasonable prediction of the droplet footprint after the spreading phase, the final fluid surface can be determined without having to solve the full fluid problem which is both time consuming and complex. The general framework was developed, then validated through comparison with prior literature as well as the modeling presented in this work. Additionally, the method was compared with other MJ modeling approaches found in literature and shown to predict the as-fabricated surface most accurately. The model was then used to explore representative mesoscale features which consisted of thousands of simulated droplets. These simulated mesoscale features showed similar deformations to the physical features printed, like rounded edge deformations, suggesting that the driving cause is likely the asymmetric deposition spread near the edge. Finally, a simulation-based investigation is undertaken to look specifically at the ideal design for novel press fabric membrane layers. The results showed that rather simple designs can promote one directional flow. To further improve the one directional flow, an active “check-valve” design is developed. Flow simulations showed significant promise for promoting one directional flow. A physical specimen of the “check-valve” design was fabricated at 2X scale. Simulated compression of the prototype showed opening of the area as intended. These simulations and findings should guide future development of press fabric constructions and merit physical testing to validate their performance.
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