A Parametric Interpolation Framework for 1D Scalar Conservation Laws using the Equal Area Principle
This provides a novel numerical method for conservation laws, but its impact is limited to 1D scalar problems and requires exact representation of initial conditions.
The paper develops a parametric interpolation framework for solving 1D scalar conservation laws by combining the method of characteristics with the equal area principle, achieving machine precision in shock position for Burgers' equation when the initial condition is exactly representable in the chosen polynomial space.
In this paper we develop a novel framework for numerically solving scalar conservation laws in one space dimension. Utilizing the method of characteristics in conjunction with the equal area principle we develop an approach where the weak solution is obtained purely as the solution of a parametric interpolation problem. As this framework hinges on the validity of the equal area principle, we provide a rigorous discussion of the equal area principle and show that, indeed, the equal area principle is equivalent to the Rankine-Hugoniot condition, within the specific context studied in this paper. Combining these results with properties of the characteristic equations yields the desired setting to define the equivalent parametric interpolation problem. We conclude by applying this framework to Burgers' equation and show how one obtains machine precision in the shock position when the initial condition can be represented exactly in the chosen space of parametric polynomials.