Pieter Van Leemput

Accuracy of Hybrid Lattice Boltzmann/Finite Difference Schemes for Reaction-Diffusion Systems

In this article we construct a hybrid model by spatially coupling a lattice Boltzmann model (LBM) to a finite difference discretization of the partial differential equation (PDE) for reaction-diffusion systems. Because the LBM has more variables (the particle distribution functions) than the PDE (only the particle density), we have a one-to-many mapping problem from the PDE to the LBM domain at the interface. We perform this mapping using either results from the Chapman–Enskog expansion or a pointwise iterative scheme that approximates these analytical relations numerically. Most importantly, we show that the global spatial discretization error of the hybrid model is one order less accurate than the local error made at the interface. We derive closed expressions for the spatial discretization error at steady state and verify them numerically for several examples on the one-dimensional domain.

Mesoscale analysis of the equation-free constrained runs initialization scheme

In this article, we analyze the stability, convergence, and accuracy of the constrained runs initialization scheme for a mesoscale lattice Boltzmann model (LBM). This type of initialization scheme was proposed by Gear and Kevrekidis in [J. Sci. Comput., 25 (2005), pp. 17–28] in the context of both singularly perturbed ordinary differential equations and equation-free computing. It maps the given macroscopic initial variables to the higher-dimensional space of microscopic/mesoscopic variables. The scheme performs short runs with the microscopic/mesoscopic simulator and resets the macroscopic variables (typically the lower order moments of the microscopic/mesoscopic variables), while leaving the higher order moments unchanged. We use the LBM Bhatnagar–Gross–Krook (BGK) model for one-dimensional reaction-diffusion systems as the microscopic/mesoscopic model. For such systems, we prove that the constrained runs scheme is unconditionally stable and that it converges to an approximation of the slaved state, i.e...

Accuracy and Stability of the Coarse Time-Stepper for a Lattice Boltzmann Model

The equation-free framework for multiscale computing is built around the central idea of a coarse time-stepper, which is an approximate time integrator for the unavailable macroscopic model when only a microscopic simulator is given. In this paper, we study the numerical properties of the coarse time-stepper when a lattice Boltzmann model for one-dimensional diffusion is used as the microscopic simulator. We derive analytical expressions for the accuracy and stability of the coarse time-stepper, which allow us to study the influence of various aspects involved in its construction.

Smooth initialization of lattice Boltzmann schemes

Lattice Boltzmann methods are paradigmatic discrete evolutions with incomplete initial conditions. This is due to the fact that the variables of the (mesoscopic) method outnumber the variables of the (macroscopic) problem to be solved. In such situations, most initializations which are compatible with the given macroscopic data lead to solutions with oscillatory or steep initial layers. In order to reduce such initial effects, we present a general approach to construct initial values which are compatible with the partial information available, and which guarantee a smooth start of the evolution. Our smoothness condition prescribes the unknown initial values as the polynomial backward extrapolation of the values obtained from a few time steps. Specifically for constant and linear extrapolation, we study the consistency, stability and accuracy of the approach in the case of a lattice Boltzmann method for one-dimensional advection. Moreover, the applicability of a simple iteration scheme as the solution method is investigated.

Numerical bifurcation analysis of lattice Boltzmann models: A reaction-diffusion example

We study two strategies to perform a time stepper based numerical bifurcation analysis of systems modeled by lattice Boltzmann methods, one using the lattice Boltzmann model as the time stepper and the other the coarse-grained time stepper proposed in Kevrekidis et al., CMS 1(4). We show that techniques developed for time stepper based numerical bifurcation analysis of partial differential equations (PDEs) can be used for lattice Boltzmann models as well. The results for both approaches are also compared with an equivalent PDE description.