Brisa N. Davis

Brisa N. Davis, Randall J. LeVeque

One difficulty in developing numerical methods for hyperbolic systems of conservation laws is the fact that solutions often contain regions where much higher resolution is required than elsewhere in the domain, particularly since the solution may contain discontinuities or other localized features. The Clawpack software deals with this issue by using block-structured adaptive mesh refinement to selectively refine around propagating waves. For problems where only a target area of the total solution is of interest, a method that allows identifying and refining the grid only in regions that influence this target area would significantly reduce the computational cost of finding a solution. In this work, we show that solving the time-dependent adjoint equation and using a suitable inner product with the forward solution allows more precise refinement of the relevant waves. We present acoustics examples in one and two dimensions and a tsunami propagation example. To perform these simulations, the use of the adjoint method has been integrated into the adaptive mesh refinement strategy of the open source Clawpack and GeoClaw software. We also present results that show that the accuracy of the solution is maintained and the computational time required is significantly reduced through the integration of the adjoint method into AMR.

Brisa N Davis, Randall J LeVeque

Adaptive mesh refinement (AMR) is often used when solving time-dependent partial differential equations using numerical methods. It enables time-varying regions of much higher resolution, which can be used to track discontinuities in the solution by selectively refining around those areas. The open source Clawpack software implements block-structured AMR to refine around propagating waves in the AMRClaw package. For problems where the solution must be computed over a large domain but is only of interest in a small area this approach often refines waves that will not impact the target area. We seek a method that enables the identification and refinement of only the waves that will influence the target area. Here we show that solving the time-dependent adjoint equation and using a suitable inner product allows for a more precise refinement of the relevant waves. We present the adjoint methodology in general, and give details on how this method has been implemented in AMRClaw. Examples for linear acoustics equations are presented, and a computational performance analysis is conducted. The adjoint method is compared to AMR methods already available in the AMRClaw software, and the resulting advantages and disadvantages are discussed. The code for the examples presented is archived on Github.