Numerical study of texture in material extrusion: Orientation in a multicomponent system of spheres and ellipsoids

Dietemann, Bastien; Bosna, Fatih; Lorenz, Mylena; Travitzky, Nahum; Kruggel‐Emden, Harald; Kraft, Torsten; Bierwisch, Claas

doi:10.1016/j.jnnfm.2021.104532

Cited by 2 publications

(6 citation statements)

References 64 publications

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“…We move on to study the amount of reorientation as a function of the composition, aspect ratio, and position within a 250

filament, as shown in Figure 10 . This figure consists of two subfigures that are composed similarly, but show different processing steps: Subfigure (a) quantifies the reorientation that occurred during the extrusion process itself as predicted in another work [ 9 , 45 ]; Subfigure (b) quantifies the reorientation that occurred during drying as measured in this work. Each row represents a constant aspect ratio, which is indicated at the very left of Subfigure (a).…”

Section: Resultsmentioning

confidence: 98%

“…The auxiliary zoom into the filament shows the spheres as transparent to allow the inspection of the individually colored platelets. The initial orientation tensor within the filament was derived from previous works [ 9 ] in which the orientation was predicted based the process history. It could be shown that the orientation tensor varied spatially with the filament height.…”

Section: Methodsmentioning

confidence: 99%

“…Therefore, a prediction of the particle orientation after an extrusion process is the topic of ongoing research. However, while there exist a burgeoning number of analytical orientation prediction models (OPMs) [ 3 , 4 , 5 , 6 , 7 , 8 ] or microscopic simulations [ 9 , 10 , 11 ] to predict such a particle orientation within the still-wet filament, little is known about the magnitude of particle reorientation in robocasted filaments during the drying step. Experimentally, information on particle reorientation is difficult to address as the particle orientation can only be measured after the sintering step, before which, however, the liquid phase must have already been removed.…”

Section: Introductionmentioning

confidence: 99%

“…Such a strategy has also been applied elsewhere [ 38 , 39 , 40 , 41 , 42 , 43 , 44 ]; the main difference from those works is that the start configuration in this work consisted of a highly filled (3D) system of particles composed exactly as applied for the robocasting process. The initial orientation of the particles within the filament was predicted numerically taking into account the process history during robocasting [ 9 ]. Such an orientation can also be predicted with the help of analytical OPMs, which have become a standard tool within extrusion processes [ 45 ].…”

Section: Introductionmentioning

confidence: 99%

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Reorientation of Suspended Ceramic Particles in Robocasted Green Filaments during Drying

et al. 2022

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This work considers the fabrication of ceramic parts with the help of an additive manufacturing process, robocasting, in which a paste with suspended particles is robotically extruded. Within the final part, the material properties depend on the orientation of the particles. A prediction of the particle orientation is challenging as the part usually undergoes multiple processing steps with varying contributions to the orientation. As the main contribution to the final particle orientation arises from the extrusion process, many corresponding prediction models have been suggested. Robocasting involves, however, further processing steps that are less studied as they have a smaller influence on the orientation. One of the processing steps is drying by natural convection, which follows directly after the extrusion process. A quantification of the reorientation that occurs during drying is mostly unknown and usually neglected in the models. Therefore, we studied the amount of reorientation of suspended particles in robocasted green filaments during drying in detail. For our study, we applied the discrete element method, as it meets various requirements: The exact particle geometry can be resolved precisely; particle–particle interactions can be described; the paste composition is reproduced exactly; the initial particle orientation can be set in accordance with the prediction from the analytical models for the extrusion part; macroscopic force laws exist to represent capillary forces due to the remaining fluid phase that remains during drying. From our study, we concluded that the magnitude of particle reorientation during drying is small compared to the orientation occurring during the extrusion process itself. Consequently, reorientation during drying might further be neglected within analytical orientation prediction models.

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“…We move on to study the amount of reorientation as a function of the composition, aspect ratio, and position within a 250

Section: Resultsmentioning

confidence: 98%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Reorientation of Suspended Ceramic Particles in Robocasted Green Filaments during Drying

et al. 2022

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“…The algorithm and setup for the suspension simulations are precisely described and validated in reference [38]. A validation to an experiment showing that the model is able to predict the orientation accurately is presented in reference [39]. For the sake of brevity, we only summarize the fundamentals and refer the reader to the references for a deeper understanding of the scheme.…”

Section: Suspension Simulationsmentioning

confidence: 99%

Assessment of Analytical Orientation Prediction Models for Suspensions Containing Fibers and Spheres

et al. 2021

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Analytical orientation models like the Folgar Tucker (FT) model are widely applied to predict the orientation of suspended non-spherical particles. The accuracy of these models depends on empirical model parameters. In this work, we assess how well analytical orientation models can predict the orientation of suspensions not only consisting of fibers but also of an additional second particle type in the shape of disks, which are varied in size and filling fraction. We mainly focus on the FT model, and we also compare its accuracy to more complex models like Reduced-Strain Closure model (RSC), Moldflow Rotational Diffusion model (MRD), and Anisotropic Rotary Diffusion model (ARD). In our work, we address the following questions. First, can the FT model predict the orientation of suspensions despite the additional particle phase affecting the rotation of the fibers? Second, is it possible to formulate an expression for the sole Folgar Tucker model parameter that is based on the suspension composition? Third, is there an advantage to choose more complex orientation prediction models that require the adjustment of additional model parameters?

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Numerical study of texture in material extrusion: Orientation in a multicomponent system of spheres and ellipsoids

Cited by 2 publications

References 64 publications

Reorientation of Suspended Ceramic Particles in Robocasted Green Filaments during Drying

Reorientation of Suspended Ceramic Particles in Robocasted Green Filaments during Drying

Assessment of Analytical Orientation Prediction Models for Suspensions Containing Fibers and Spheres

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