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Lax–Friedrichs method

Mathematical method From Wikipedia, the free encyclopedia

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The Lax–Friedrichs method, named after Peter Lax and Kurt O. Friedrichs, is a numerical method for the solution of hyperbolic partial differential equations based on finite differences. The method can be described as the FTCS (forward in time, centered in space) scheme with a numerical dissipation term of 1/2. One can view the Lax–Friedrichs method as an alternative to Godunov's scheme, where one avoids solving a Riemann problem at each cell interface, at the expense of adding artificial viscosity.

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Illustration for a Linear Problem

Consider a one-dimensional, linear hyperbolic partial differential equation for of the form: on the domain with initial condition and the boundary conditions

If one discretizes the domain to a grid with equally spaced points with a spacing of in the -direction and in the -direction, we introduce an approximation of where are integers representing the number of grid intervals. Then the Lax–Friedrichs method to approximate the partial differential equation is given by:

Or, rewriting this to solve for the unknown

Where the initial values and boundary nodes are taken from

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Extensions to Nonlinear Problems

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A nonlinear hyperbolic conservation law is defined through a flux function :

In the case of , we end up with a scalar linear problem. Note that in general, is a vector with equations in it. The generalization of the Lax-Friedrichs method to nonlinear systems takes the form[1]

This method is conservative and first order accurate, hence quite dissipative. It can, however be used as a building block for building high-order numerical schemes for solving hyperbolic partial differential equations, much like Euler time steps can be used as a building block for creating high-order numerical integrators for ordinary differential equations.

We note that this method can be written in conservation form: where

Without the extra terms and in the discrete flux, , one ends up with the FTCS scheme, which is well known to be unconditionally unstable for hyperbolic problems.

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Stability and accuracy

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Example problem initial condition
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Lax-Friedrichs solution

This method is explicit and first order accurate in time and first order accurate in space ( provided are sufficiently-smooth functions. Under these conditions, the method is stable if and only if the following condition is satisfied:

(A von Neumann stability analysis can show the necessity of this stability condition.) The Lax–Friedrichs method is classified as having second-order dissipation and third order dispersion.[2] For functions that have discontinuities, the scheme displays strong dissipation and dispersion;[3] see figures at right.

References

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