Speaker
Description
Discontinuous fiber-reinforced composites offer a high potential for lightweight applications due to their favorable specific stiffness and design freedom. Micro-CT imaging reveals that their microstructure is highly anisotropic, random and heterogeneous, which needs to be considered to predict their mechanical properties properly. For such materials, computational multiscale methods are capable tools, relying on representative geometrical descriptions of the microstructure. However, to use these methods, synthetic microstructures representing the considered materials are necessary first. For long fiber reinforced composites, the microstructure is mainly described by the fiber volume fraction, the fiber length and orientation distributions as well as the fiber curvature [1]. To realize the fiber curvature of long fiber reinforced composites, the fused sequential additional and migration (fSAM) method [2] models the fibers as polygonal chains. Based on an optimization scheme, the method is searching for non-penetrating fiber arrangements which fulfil the further desired descriptors, e.g., the fiber orientation distribution. As the polygonal chains are defined on a curved manifold, an adapted gradient descent scheme is applied moving along the geodesics, i.e., the shortest lines between two points on the manifold. The fSAM algorithm prevents unrealistically high fiber bending by restricting the angles between adjacent segments. However, besides this angle control, the fSAM algorithm does not account for the degree of fiber curvature even if this property may influence the mechanical behavior of the microstructure. Thus, we present an extension of the fSAM algorithm to account for the fiber curvature as desired quantity. Therefore, we first discuss the implemented curvature measure for polygonal chains. Then, we introduce the adapted objective function to account for the desired degree of curvature and present the algorithmic choices within the fSAM algorithm to realize microstructures with varying degrees of curvature. Based on the extended fSAM algorithm, we conduct numerical studies with respect to the influence of the curvature on the effective properties of long fiber reinforced composites.
Discontinuous fiber-reinforced composites offer a high potential for lightweight applications due to their favorable specific stiffness and design freedom. Micro-CT imaging reveals that their microstructure is highly anisotropic, random and heterogeneous, which needs to be considered to predict their mechanical properties properly. For such materials, computational multiscale methods are capable tools, relying on representative geometrical descriptions of the microstructure. However, to use these methods, synthetic microstructures representing the considered materials are necessary first. For long fiber reinforced composites, the microstructure is mainly described by the fiber volume fraction, the fiber length and orientation distributions as well as the fiber curvature [1]. To realize the fiber curvature of long fiber reinforced composites, the fused sequential additional and migration (fSAM) method [2] models the fibers as polygonal chains. Based on an optimization scheme, the method is searching for non-penetrating fiber arrangements which fulfil the further desired descriptors, e.g., the fiber orientation distribution. As the polygonal chains are defined on a curved manifold, an adapted gradient descent scheme is applied moving along the geodesics, i.e., the shortest lines between two points on the manifold. The fSAM algorithm prevents unrealistically high fiber bending by restricting the angles between adjacent segments. However, besides this angle control, the fSAM algorithm does not account for the degree of fiber curvature even if this property may influence the mechanical behavior of the microstructure. Thus, we present an extension of the fSAM algorithm to account for the fiber curvature as desired quantity. Therefore, we first discuss the implemented curvature measure for polygonal chains. Then, we introduce the adapted objective function to account for the desired degree of curvature and present the algorithmic choices within the fSAM algorithm to realize microstructures with varying degrees of curvature. Based on the extended fSAM algorithm, we conduct numerical studies with respect to the influence of the curvature on the effective properties of long fiber reinforced composites.
References:
[1] S. Fliegener, M. Luke, and P. Gumbsch: 3D microstructure modeling of long fiber reinforced thermoplastics. Composites Science and Technology, 104, 136-145 (2014).
[2] C. Lauff, M. Schneider, J. Montesano, and T. Böhlke: Generating microstructures of long fiber reinforced composites by the fused sequential addition and migration method. International Journal for Numerical Methods in Engineering, 125(22), e7573 (2024).
