Random-walk-based stochastic modeling of three-dimensional fiber systems

Area of Science:

• Materials Science
• Computational Modeling
• Statistical Physics

Background:

• Existing stochastic models for fiber systems have limitations in controlling fiber bending and orientation distributions.
• A need exists for models that can generate dense, nonoverlapping fiber configurations with precise parameter control.

Purpose of the Study:

• To introduce a new generalized force-biased packing stochastic model for simulating fiber systems.
• To enable controllable bending and orientation distributions in dense fiber configurations.

Main Methods:

• Fibers are represented as chains of balls generated via random walks with parameters from a multivariate von Mises-Fisher distribution.
• A balance of repulsion and recovery forces is used to achieve equilibrium, preventing fiber crossing and maintaining structure.

Main Results:

• The model successfully generates dense, nonoverlapping fiber systems.
• High volume fractions, up to 72.0075%, were achieved.
• The model allows for controllable fiber bending and orientation distributions.

Conclusions:

• The novel stochastic model effectively simulates dense fiber systems with controlled properties.
• This approach overcomes limitations of previous models, offering greater flexibility and precision.