Issue |
ESAIM: M2AN
Volume 57, Number 5, September-October 2023
|
|
---|---|---|
Page(s) | 3061 - 3090 | |
DOI | https://doi.org/10.1051/m2an/2023077 | |
Published online | 20 October 2023 |
The regularised inertial Dean–Kawasaki equation: discontinuous Galerkin approximation and modelling for low-density regime
1
Institute of Science and Technology Austria (ISTA), Am Campus 1, 3400 Klosterneuburg, Austria, up to 30th September 2023
2
University of Bath, Bath BA2 7AY, UK
* Corresponding author: fc402@bath.ac.uk
Received:
21
July
2022
Accepted:
12
September
2023
The Regularised Inertial Dean–Kawasaki model (RIDK) – introduced by the authors and J. Zimmer in earlier works – is a nonlinear stochastic PDE capturing fluctuations around the meanfield limit for large-scale particle systems in both particle density and momentum density. We focus on the following two aspects. Firstly, we set up a Discontinuous Galerkin (DG) discretisation scheme for the RIDK model: we provide suitable definitions of numerical fluxes at the interface of the mesh elements which are consistent with the wave-type nature of the RIDK model and grant stability of the simulations, and we quantify the rate of convergence in mean square to the continuous RIDK model. Secondly, we introduce modifications of the RIDK model in order to preserve positivity of the density (such a feature only holds in a “high-probability sense” for the original RIDK model). By means of numerical simulations, we show that the modifications lead to physically realistic and positive density profiles. In one case, subject to additional regularity constraints, we also prove positivity. Finally, we present an application of our methodology to a system of diffusing and reacting particles. Our Python code is available in open-source format.
Mathematics Subject Classification: 60H15 / 65N30 / 35R60 / 65N99
Key words: Stochastic PDEs of fluctuating hydrodynamics / Regularised Inertial Dean–Kawasaki model / Discontinuous Galerkin FEM / positivity-preserving schemes / reacting diffusing agents
© The authors. Published by EDP Sciences, SMAI 2023
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