Efficient Graph-based Tensile Strength Simulations of Random Fiber Structures

TL;DR

This paper introduces a graph-based simulation framework for efficiently modeling the tensile strength of random fiber structures in nonwoven materials, addressing multi-scale and stochastic complexities.

Contribution

It presents a novel graph-truss model with nonlinear elasticity and a specialized data reduction, enabling faster and scalable tensile strength simulations of complex fiber microstructures.

Findings

Efficient simulation of fiber tensile strength with reduced computational cost.

Successful incorporation of randomness via Monte Carlo methods.

Proof of concept demonstrating potential for optimization in material design.

Abstract

In this paper, we propose a model-simulation framework for virtual tensile strength tests of random fiber structures, as they appear in nonwoven materials. The focus is on the efficient handling with respect to the problem-inherent multi-scales and randomness. In particular, the interplay of the random microstructure and deterministic structural production-related features on the macro-scale makes classical homogenization-based approaches computationally complex and costly. In our approach we model the fiber structure to be graph-based and of truss-type, equipped with a nonlinear elastic material law. Describing the tensile strength test by a sequence of force equilibria with respect to varied boundary conditions, its embedding into a singularly perturbed dynamical system is advantageous with regard to statements about solution theory and convergence of numerical methods. A problem-tailored data reduction provides additional speed-up, Monte-Carlo simulations account for the randomness. This work serves as a proof of concept and opens the field to optimization.