Biocomposite modeling by tomographic feature extraction and synthetic microstructure reconstruction. (10th November 2022)

• Record Type: Journal Article
• Authors: Verho, Tuukka; Fortino, Stefania; Hradil, Petr; Turpeinen, Tuomas; Immonen, Kirsi; Harlin, Ali; Sandquist, David
• Is Part Of: Composites science and technology. Volume 230(2022)Part 1
• Publication Date: 2022-11-10
• Subjects: Natural fibre composites A -- X-ray computed tomography D -- Representative volume element (RVE) C -- Finite element analysis (FEA) C -- Elastic properties B; Composite materials -- Periodicals; Composite materials; Fibrous composites; Periodicals; 620.118
• DOI: 10.1016/j.compscitech.2022.109713
• Languages: English
• ISSNs: 0266-3538

Abstract

Abstract: In comparison to established glass and carbon fiber models, creating a representative volume element to perform finite element analysis for a biocomposite is a complex undertaking. As the fibers appear in a variety of lengths, shapes and orientations, many parameters are needed to describe the microstructure, and a large sample of fibers is needed for a statistically representative RVE. In this study, we present an analysis procedure based on X-ray microtomography to obtain morphological statistics of biofibers in a composite as well as a synthetic microstructure reconstruction and numerical analysis methodology. To obtain statistics on individual fibers from microtomography images, we apply a dual-threshold segmentation approach and fiber backbone tracking. A synthetic model is constructed by using size, orientation and shape statistics from the analysis. Non-overlapping model geometries with fiber volume fractions up to 25% are obtained by a two-stage Monte Carlo packing method. Finite element analyses with periodic boundary conditions are performed to obtain homogenized elastic moduli to be compared with experimental tests. Put together, these steps constitute a complete modeling workflow that also allows virtual design and exploration of the parameter space. Graphical abstract: Image 1