Analysis of heterogeneous Markov media for particle transport problems.
Phys Rev E
; 106(4-1): 044108, 2022 Oct.
Article
en En
| MEDLINE
| ID: mdl-36397583
ABSTRACT
Markov media provide a prototype class of stochastic geometries that are widely used in order to model several complex and disordered systems encompassing, e.g., turbulent fluids and plasma, atmospheric layers, or biological tissues, especially in relation to particle transport problems. In several key applications, the statistical properties of random media may display spatial gradients due to material stratification, which means that the typical spatial scale and the probability of finding a given material phase at a spatial location become nonhomogeneous. In this paper we investigate the main features of spatially heterogeneous Markov media, using Poisson hyperplane tessellations and Arak polygonal fields. We show that both models can generate geometry realizations sharing Markov-like properties, and discuss their distinct advantages and drawbacks in terms of flexibility and ease of use. The impact of these models on the observables related to particle transport will be assessed using Monte Carlo simulations.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Contexto en salud:
1_ASSA2030
Problema de salud:
1_financiamento_saude
Tipo de estudio:
Health_economic_evaluation
/
Prognostic_studies
Idioma:
En
Revista:
Phys Rev E
Año:
2022
Tipo del documento:
Article
País de afiliación:
Francia