https://popups.uliege.be/esaform21/index.php?id=361 Publications of Auteurs Luise Kärger fr 0 https://popups.uliege.be/esaform21/index.php?id=3882 Manufacturing process optimisation usually amounts to searching optima in high-dimensional parameter spaces. In industrial practice, this search is most often directed by human-subjective expert judgment and trial-and-error experiments. In contrast, high-fidelity simulation models in combination with general-purpose optimisation algorithms, e.g. finite element models and evolutionary algorithms, enable a methodological, virtual process exploration and optimisation. However, reliable process models generally entail significant computation times, which often renders classical, iterative optimisation impracticable. Thus, efficiency is a key factor in optimisation. One option to increase efficiency is surrogate-based optimisation (SBO): SBO seeks to reduce the overall computational load by constructing a numerically inexpensive, data-driven approximation („surrogate“) of the expensive simulation. Traditionally, classical regression techniques are applied for surrogate construction. However, they typically predict a predefined, scalar performance metric only, which limits the amount of usable information gained from simulations. The advent of machine learning (ML) techniques introduces additional options for surrogates: in this work, a deep neural network (DNN) is trained to predict the full strain field instead of a single scalar during textile forming („draping“). Results reveal an improved predictive accuracy as more process-relevant information from the supplied simulations can be extracted. Application of the DNN in an SBO- framework for blank holder optimisation shows improved convergence compared to classical evolutionary algorithms. Thus, DNNs are a promising option for future surrogates in SBO. Mon, 29 Mar 2021 14:55:15 +0200 Thu, 08 Apr 2021 21:19:38 +0200 https://popups.uliege.be/esaform21/index.php?id=3882 https://popups.uliege.be/esaform21/index.php?id=2056 During forming of complex fiber-metal laminates (FML), compressive stress zones occur. In pure textile forming, these compressive stresses typically lead to extensive wrinkling. In FML forming, however, wrinkling is partly hindered by the metal layers. Thus, combined stress states occur, where compression influences the deformation. In forming simulation, these compressive stresses can lead to erroneous formation of shear bands within the fabric layer, if the deformation behavior is not modelled correctly. Simple fabric models neither consider interactions between roving directions nor model interactions between membrane strains and shear strains. More advanced invariant-based hyperelastic material models are able to capture these interactions, but only consider tension and shear, while disregarding compression. A common assumption is to set the fabric compression stiffness close to zero. Experimentally, the in-plane fabric compression stiffness has not been determined so far. However, in FML forming, the compression stiffness and the combined compression-tension-shear behavior becomes relevant. In this article, the authors summarize and analyze the capacity of state-of-the-art fabric material models to predict the deformation behavior of fabrics under combined loading. Based on these findings, conclusions are drawn for a new macroscopic modeling approach for woven fabrics, including coupling of tension, compression and shear. Tue, 23 Mar 2021 12:37:11 +0100 Mon, 12 Apr 2021 10:27:52 +0200 https://popups.uliege.be/esaform21/index.php?id=2056 https://popups.uliege.be/esaform21/index.php?id=1938 Wet compression molding (WCM) provides large-scale production potential for continuous fiber-reinforced structural components due to simultaneous infiltration and draping during molding. Due to thickness-dominated infiltration of the laminate, comparatively low cavity pressures are sufficient – a considerable economic advantage. Experimental and numerical investigations prove strong mutual dependencies between the physical mechanisms, especially between resin flow (mold filling) and textile forming (draping), similar to other liquid molding techniques (LCM). Although these dependencies provide significant benefits such as improved contact, draping and infiltration capabilities, they may also lead to adverse effects such as flow-induced fiber displacement. To support WCM process and part development, process simulation requires a fully coupled approach including the capability to predict critical process effects. This work aims to demonstrate the suitability of a macroscopic, fully coupled, three-dimensional process simulation approach, to predict the process behavior during WCM, including flow-induced fiber displacements. The developed fluid model is superimposed to a suitable 3D forming model, which accounts for the deformation mechanisms including non-linear transverse compaction behavior. A strong Fluid-Structure-Interaction (FSI) enforced by Terzaghi’s law is applied to assess flow-induced fiber displacements during WCM within a porous UD-NCF stack in a homogenized manner. Accordingly, resulting local deformations are considered within the pressure field. All constitutive equations are formulated with respect to fiber deformation under finite strains. Results of a parametric study underline the relevance of contact conditions within the dry and infiltrated stack. The numerically predicted results are benchmarked and verified using both own and available experimental results from literature. Tue, 23 Mar 2021 10:43:52 +0100 Mon, 12 Apr 2021 10:09:34 +0200 https://popups.uliege.be/esaform21/index.php?id=1938 https://popups.uliege.be/esaform21/index.php?id=883 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. Mon, 22 Mar 2021 09:49:49 +0100 Tue, 30 Mar 2021 09:49:12 +0200 https://popups.uliege.be/esaform21/index.php?id=883 https://popups.uliege.be/esaform21/index.php?id=355 Unidirectional non-crimp fabrics (UD-NCF) provide the highest lightweight potential among dry textile materials. Compared to multiaxial NCF, the fabric layers in UD-NCF enable a more targeted tailoring. Compared to woven fabrics, the fibres of UD-NCF are straight without weakening undulations. However, the formability of UD-NCF is more challenging compared to woven fabrics. The yarns are bonded by a stitching and the deformation behaviour highly depends on this stitching and on the slippage between the stitching and the fibre yarns. Moreover, distinct local draping effects occur, like gapping and fibre waviness, which can have a considerable impact on the mechanical performance. Such local effects are particularly challenging or even impossible to be predicted by macroscopic forming simulation. The present work applies a previously published macroscopic UD-NCF modelling approach to perform numerical forming analyses and evaluate the prediction accuracy of forming effects. In addition to fibre orientations and shear angles, as investigated in previous work, the present work also provides indication for fibre area ratios, gapping, transverse compaction and fibre waviness. Moreover, the prediction accuracy is validated by comparison with experimental tests, where full-field strains of inner plies are captured by prior application of dots onto the fibre yarns, by measuring them via radiography and applying a photogrammetry software. The modelling approach provides good prediction accuracy for fibre orientations, shear strains and fibre area ratio. Conversely, normal fibre strains, indicating fibre waviness, and transverse strains, indicating gapping, show some deviations due to the multiscale nature of UD-NCF that cannot be captured entirely on macroscopic scale. Fri, 19 Mar 2021 17:12:09 +0100 Mon, 29 Mar 2021 17:40:40 +0200 https://popups.uliege.be/esaform21/index.php?id=355