Accuracy of adaptive discontinuous Galerkin simulations

Duration: 20 mins 44 secs

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Description:	Andreas Müller, (Naval Postgraduate School) Tuesday 25 September 2012, 14:25-14:50


Created:	2012-09-26 17:11
Collection:	Multiscale Numerics for the Atmosphere and Ocean
Publisher:	Isaac Newton Institute
Copyright:	Andreas Müller
Language:	eng (English)


Abstract:	Adaptive mesh refinement generally serves to increase computational efficiency without compromising the accuracy of the numerical solution significantly. However it is an open question in which regions the spatial resolution can actually be coarsened without affecting the accuracy of the result significantly. This question is investigated for a specific example of dry atmospheric convection, namely the simulation of warm air bubbles. For this purpose a novel numerical model is developed that is tailored towards this specific meteorological problem. The compressible Euler equations are solved with a Discontinuous Galerkin method. Time integration is done with a semi-implicit approach and the dynamic grid adaptivity uses space filling curves via the AMATOS function library. The numerical model is validated with a convergence study and five standard test cases. A method is introduced which allows one to compare the accuracy between different choices of refinement regions even in a case when the exact solution is not known. Essentially this is done by comparing features of the solution that are strongly sensitive to spatial resolution. For a rising warm air bubble the additional error by using adaptivity is smaller than 1% of the total numerical error if the average number of elements used for the adaptive simulation is about 50% smaller than the number used for the simulation with the uniform fine-resolution grid. Correspondingly the adaptive simulation is almost two times faster than the uniform simulation.

Abstract:

Adaptive mesh refinement generally serves to increase computational efficiency without compromising the accuracy of the numerical solution significantly. However it is an open question in which regions the spatial resolution can actually be coarsened without affecting the accuracy of the result significantly. This question is investigated for a specific example of dry atmospheric convection, namely the simulation of warm air bubbles. For this purpose a novel numerical model is developed that is tailored towards this specific meteorological problem. The compressible Euler equations are solved with a Discontinuous Galerkin method. Time integration is done with a semi-implicit approach and the dynamic grid adaptivity uses space filling curves via the AMATOS function library. The numerical model is validated with a convergence study and five standard test cases.

A method is introduced which allows one to compare the accuracy between different choices of refinement regions even in a case when the exact solution is not known. Essentially this is done by comparing features of the solution that are strongly sensitive to spatial resolution. For a rising warm air bubble the additional error by using adaptivity is smaller than 1% of the total numerical error if the average number of elements used for the adaptive simulation is about 50% smaller than the number used for the simulation with the uniform fine-resolution grid. Correspondingly the adaptive simulation is almost two times faster than the uniform simulation.

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