A systematic approach to transforming composite 3D images into meso-scale computational models
Paper in proceeding, 2020

High performance polymer matrix composites (PMC) have a high specific stiffness and can be used to easily manufacture highly complex components. Many types of defects can occur during molding. Flaws and damage degrade the resulting mechanical properties of the composites material. It is difficult to assess the actual stiffness, strength and fatigue limit of flawed and damaged structures. Among these the fatigue limit is the most difficult to predict. Through a combination of modern imaging techniques and finite element analysis of in-situ fiber bundles, it is now becoming possible to estimate fatigue limits for polymer matrix composites structures with flaws or damage. Composite materials can be imaged with 3D X-ray Computed Tomography (CT) in a sufficient detail to view 3D fiber bundle matrix interfaces. These images can then be directly imported into physical models to be used in finite element analysis. The process of converting these images into computer models for analysis is currently extremely time consuming, difficult and subjective. The method presented here has been developed to bridge this gap.

Mechanical analysis

Modeling

Textiles

Composites

Author

Brina Blinzler

Chalmers, Industrial and Materials Science, Material and Computational Mechanics

Dennis Wilhelmsson

Chalmers, Industrial and Materials Science, Material and Computational Mechanics

Leif Asp

Chalmers, Industrial and Materials Science, Material and Computational Mechanics

Kristine M. Jespersen

Waseda University

Lars Mikkelsen

Technical University of Denmark (DTU)

ECCM 2018 - 18th European Conference on Composite Materials

18th European Conference on Composite Materials
Athens, Greece,

Subject Categories

Applied Mechanics

Textile, Rubber and Polymeric Materials

Composite Science and Engineering

Infrastructure

C3SE (Chalmers Centre for Computational Science and Engineering)

Areas of Advance

Materials Science

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1/3/2024 9