A kernel-based discretisation method for first order partial differential equations of evolution type
This work provides a novel numerical method for solving first-order PDEs, relevant to researchers in computational mathematics and physics, but the results are theoretical with limited empirical validation.
The paper introduces a new meshfree, kernel-based discretisation method for first-order PDEs of evolution type, using an Eulerian approach. It proves stability and convergence, with approximation order depending on kernel smoothness, and demonstrates the method on a 1D Burgers equation.
We derive a new discretisation method for first order PDEs of arbitrary spatial dimension, which is based upon a meshfree spatial approximation. This spatial approximation is similar to the SPH (smoothed particle hydrodynamics) technique and is a typical kernel-based method. It differs, however, significantly from the SPH method since it employs an Eulerian and not a Lagrangian approach. We prove stability and convergence for the resulting semi-discrete scheme under certain smoothness assumptions on the defining function of the PDE. The approximation order depends on the underlying kernel and the smoothness of the solution. Hence, we also review an easy way of constructing smooth kernels yielding arbitrary convergence orders. Finally, we give a numerical example by testing our method in the case of a one-dimensional Burgers equation.