Jennifer Ryan
Department of Applied Mathematics and Statistics, ÃÛÌÇÖ±²¥ School of Mines
Superconvergence Extraction: How to do it? When is it applicable?
Many numerical simulations produce data that contains hidden information. This hidden information can be exploited to create even more accurate representations of the data by appropriately constructing convolution post-processors. In this presentation we introduce the Smoothness-Increasing Accuracy-Conserving (SIAC) post-processing filter. This post-processing filter takes advantage of the information hidden in the numerical solution making it more accurate. This presentation will focus on identifying where this hidden accuracy comes from, why the hidden accuracy is important, and different methods of applicability.