Abstract
We make an analytic study of the diffusive, dispersive and overall errors, which arise when using semiimplicit semiLagrangian (SISL) finite difference methods to approximate those travelling wave solutions of the onedimensional Burgers' equation with small diffusion, which develop sharp fronts. For the case of a fixed uniform spatial mesh, with piecewise linear interpolation, a backward error analysis approach is used to construct a precise formal analytic description of the front profile of the numerical approximation to this solution. From this description it is possible to obtain precise estimates of the front width and the front speed in terms of the spatial and temporal step size and to express the overall solution error in terms of these. These formal estimates agree closely with numerical calculations, both qualitatively and quantitatively, and display a roughly periodic behaviour as the number N_{x} of mesh points increases, and the CFL number passes through integer values. In particular, they show that despite the otherwise poor resolution of the method, the front width is closely approximated when the CFL number is close to an integer, and the front speed is closely approximated when it is close to a half integer. The overall L_{2} error also shows superconvergence for certain values of N_{x}. This possibly motivates doing two calculations with different N_{x} when using the SISL method on such problems to separately minimise the diffusive and dispersive errors. Similar errors in the front width and speed are observed for a number of different interpolation schemes with and without flux limiters.
Original language  English 

Pages (fromto)  261282 
Number of pages  22 
Journal  Applied Numerical Mathematics 
Volume  145 
Early online date  21 Jun 2019 
DOIs  
Publication status  Published  1 Nov 2019 
Keywords
 Burgers' equation
 Error estimates
 Modified equation
 Numerical weather prediction
 Semiimplicit
 SemiLagrangian
ASJC Scopus subject areas
 Numerical Analysis
 Computational Mathematics
 Applied Mathematics
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Chris Budd
 Department of Mathematical Sciences  Professor
 EPSRC Centre for Doctoral Training in Statistical Applied Mathematics (SAMBa)
 Probability Laboratory at Bath
 Centre for Doctoral Training in Decarbonisation of the Built Environment (dCarb)
 Centre for Mathematical Biology
 Institute for Mathematical Innovation (IMI)
Person: Research & Teaching