Size Effects in Random Fiber Networks Controlled by the Use of Generalized Boundary Conditions

Area of Science:

• Materials Science
• Computational Mechanics
• Biomechanics

Background:

• Stochastic fiber networks are prevalent in engineering and biology.
• These materials exhibit multiscale heterogeneity, leading to size-dependent properties.
• Evaluating mechanical responses often requires large computational models.

Purpose of the Study:

• To quantify the size effect on linear and non-linear mechanical responses of 3D stochastic fiber networks.
• To understand the dependence of this size effect on material parameters and network deformation affinity.
• To develop a computational method for accurate prediction using smaller models.

Main Methods:

• Analysis of size effect in both affine and non-affine 3D stochastic fiber networks.
• Adaptation of generalized boundary conditions for fibrous materials.
• Numerical evaluation of mechanical properties at small and large strains.

Main Results:

• The size effect is more significant in non-affine networks compared to affine ones.
• The size effect diminishes slowly with increasing model size.
• The proposed method enables accurate prediction of network behavior with smaller models.

Conclusions:

• Generalized boundary conditions offer an effective approach to mitigate the computational burden of size effects in fiber network simulations.
• This method allows for accurate prediction of mechanical responses, essential for designing and understanding these complex materials.
• The findings are applicable to both synthetic and biological fibrous materials.