Modeling advection on distance-weighted directed networks

In this paper, we propose a model for describing advection dynamics on distance-weighted directed graphs. To this end we establish a set of key properties, or axioms, that a discrete advection operator should satisfy, and prove that there exists an essentially unique operator satisfying all such properties. Both infinite and finite networks are considered, as well as possible variants and extensions. We illustrate the proposed model through examples, both analytical and numerical, and we describe an application to the simulation of a traffic network.

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Publication Details

Journal
Mathematical Models and Methods in Applied Sciences
Published
2025-02-07
DOI
https://doi.org/10.1142/s0218202525500162
Citations
1
Primary Topic
Neural Networks and Applications
Type
article
Field-Weighted Citation Impact
2.48
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article

Modeling advection on distance-weighted directed networks

Fabio Durastante, Michele Benzi, Francesco Zigliotto
1 citations
Mathematical Models and Methods in Applied Sciences
Neural Networks and Applications
2.48
article

Modeling advection on distance-weighted directed networks

Fabio Durastante, Michele Benzi, Francesco Zigliotto
article en
1 citations

Abstract

In this paper, we propose a model for describing advection dynamics on distance-weighted directed graphs. To this end we establish a set of key properties, or axioms, that a discrete advection operator should satisfy, and prove that there exists an essentially unique operator satisfying all such properties. Both infinite and finite networks are considered, as well as possible variants and extensions. We illustrate the proposed model through examples, both analytical and numerical, and we describe an application to the simulation of a traffic network.

Mathematical Models and Methods in Applied SciencesVol. 35(05)
University of Pisa (IT), Scuola Normale Superiore (IT)
Climate action
Openalex Percentile: Top 12%
Neural Networks and Applications
2.48
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