Thermal Modeling of Laser Powder Bed Fusion during Printing on Temperature-Unstable Materials Considering Local Sintering

The integration of local metal structures into polymer components using Laser Powder Bed Fusion (PBF-LB/M) offers great potential regarding multifunctional lightweight structures. However, such process hybridization involves huge challenges. In order to reduce the temperature input into the less temperature-resistant materials, the use of lower laser powers in the interfacial region is essential. The resulting local sintering of the metal powder affects the thermal properties in the interfacial region, leading to a change in heat dissipation in the temperature-unstable material. A modeling approach oriented to selective laser sintering is presented for predicting the degree of sintering and associated thermal properties in the context of PBF-LB/M process simulation

Formability Assessment of Variable Geometries Using Machine Learning - Analysis of the Influence of the Database

Surrogate modelling has proven to be an effective strategy for time-efficient analysis and optimisation of expensive functions such as manufacturing process simulations. However, most surrogate approaches generate problem-specific “one-off” models, which cannot be reused in other, even similar scenarios. Hence, variations of the problem, e.g. minor geometry changes, instantly invalidate the surrogate. Image-based machine learning (ML) techniques have been proposed as an option to train a surrogate for variable geometries. However, it is currently unclear how to construct a sufficiently diverse set of generic training geometries and what effect different databases have. This work investigates the effect of different databases on the prediction accuracy of an ML-assessment of component manufacturability. The considered use-case is textile forming (draping) of a woven fabric. Sampling plans generate different numbers of training geometries, which are in turn evaluated in draping simulations. An image-based ML-algorithm is trained on these process samples and evaluated on a set of validation geometries. Results show that the diversity of the training geometries has a greater impact on the prediction accuracy than the number of samples. The results also hint that a comparably low number of geometry samples suffices to give meaningful results. With these findings, ML-techniques are considered a promising and time-efficient tool for manufacturability assessment at early stages of part and process design

Theoretical approximation of hydrodynamic and fiber-fiber interaction forces for macroscopic simulations of polymer flow process with fiber orientation tensors

Flow processes of discontinuous fiber reinforced polymers (FRPs) are the essence of several polymer-based manufacturing processes. FRPs show a transient chemo-thermomechanical matrix behavior and fiber-induced anisotropic physical properties. Therefore, they are one of the most complex materials used in volume production. The general flow behavior is influenced by fibers and their interactions with the matrix and other fibers. The consideration of individual fibers is numerically not capable for process simulation of FRP parts. Therefore, orientation tensors are used in macroscopic simulations, leading to a loss of information about the fiber network. Within this work, novel approximation schemes are presented to determine hydrodynamic and fiber-fiber contact forces with information provided by the second order fiber orientation tensor. Approximation of these forces can henceforth facilitate fiber breakage modeling in macroscopic process simulations. The results are verified by numerical simulations with individual fibers of different orientation states and lengths, showing good agreement with the verification results

Potential and challenges of a solid-shell element for the macroscopic forming simulation of engineering textiles

Finite element (FE) forming simulation offers the possibility of a detailed analysis of the deformation behaviour of engineering textiles during forming processes, to predict possible manufacturing effects such as wrinkling or local changes in fibre volume content. The majority of macroscopic simulations are based on conventional two-dimensional shell elements with large aspect ratios to model the membrane and bending behaviour of thin fabrics efficiently. However, a three-dimensional element approach is necessary to account for stresses and strains in thickness direction accurately, which is required for processes with a significant influence of the fabric’s compaction behaviour, e.g. wet compression moulding. Conventional linear 3D-solid elements that would be commercially available for this purpose are rarely suitable for high aspect ratio forming simulations. They are often subjected to several locking phenomena under bending deformation, which leads to a strong dependence of the element formulation on the forming behaviour [1]. Therefore, in the present work a 3D hexahedral solid-shell element, based on the initial work of Schwarze and Reese [2,3], which has shown promising results for the forming of thin isotropic materials [1], is extended for highly anisotropic materials. The advantages of a locking-free element formulation are shown through a comparison to commercially available solid and shell elements in forming simulations of a generic geometry. Additionally, first ideas for an approach of a membrane-bending-decoupling based on a Taylor approximation of the strain are discussed, which is necessary for an accurate description of the deformation behaviour of thin fabrics

Influence of fiber breakage on flow behavior in fiber length- and orientation-dependent injection molding simulations

Injection molding is one of the most important processes for manufacturing discontinuous fiber reinforced polymers (FRPs). The matrix of FRPs shows a transient chemo-thermomechanical behavior and the fibers create anisotropy influencing physical properties. Hence, FRPs are complex materials, but also likely used in volume production. In this work, the fiber-induced anisotropic behavior during mold filling is modelled with an anisotropic fourth order viscosity tensor. The viscosity tensor takes second and fourth order fiber orientation tensor, fiber length and non-Newtonian matrix viscosity into account. In this way, the macroscopic simulation captures the influence of the flow field on the fiber re-orientation and vice versa. The fiber orientation tensor is used to determine reference fibers in every element for calculation of hydrodynamic forces. This information is used in a novel fiber breakage model, based on buckling of fibers in Jeffery’s orbit. The result is a macroscopic molding simulation with not only transient fiber orientation distribution, but also fiber length distribution. Due to the anisotropic viscosity tensor, the predicted fiber breakage influences the material’s viscosity and flow behavior, which is also visible in the simulated cavity pressure. The results are validated with injection molding experiments, performed with a glass fiber reinforced phenolic compound, showing good agreement