Transport in two-dimensional scattering stochastic media: simulations and models

Area of Science:

• Physics
• Computational Physics
• Materials Science

Background:

• Understanding particle transport in complex media is crucial for various scientific fields.
• Stochastic media present unique challenges due to their random and heterogeneous nature.
• Classical transport phenomena require robust modeling techniques.

Purpose of the Study:

• To investigate classical transport of neutral particles in two-dimensional purely scattering stochastic media.
• To develop and validate partial Markovian models for describing transport processes.
• To compare simulation results with model predictions for accuracy.

Main Methods:

• Numerical Monte Carlo simulations were employed to model transport in 2D stationary, binary, purely scattering stochastic media.
• Markovian mixing statistics were utilized to define the stochastic properties of the media.
• Partial Markovian descriptions were developed as analytical models for the transport phenomena.

Main Results:

• Monte Carlo simulations provided detailed insights into particle transport dynamics.
• The proposed partial Markovian models demonstrated good agreement with simulation outcomes.
• The correlation length scale within the stochastic media was a key factor in model accuracy.

Conclusions:

• Partial Markovian descriptions serve as effective models for neutral particle transport in 2D stochastic scattering media.
• The findings validate the use of these models for predicting transport behavior in systems with correlated heterogeneity.
• This research contributes to the understanding of transport phenomena in complex, disordered materials.