Beginning Fall 2025
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Meeting ID 863 7686 1836 Passcode SS_DERR333
https://txstate.zoom.us/j/86376861836?pwd=MuhOetE19T5FEcaby8gqQ3TlZD6PZa.1
Click here for more informationSpeaker: Professor Jennifer K. Ryan, KTH Royal Institute of Technology, Division Head of Numerical Analysis, Optimization, and Systems Theory at the Department of Mathematics
Filtering is an important tool to aid in reducing non-physical oscillations, errors, and the amount of data necessary for accurate simulations. Further, the ability to utilize filtering can allow for interaction between processes that occur at different scales. However, filtering for solutions containing sharp gradients can be particularly challenging. Advances in filtering for sharp-gradients, including utilizing non-symmetric filtering, has become increasingly necessary in order to understand the detailed physics in applications such as hypersonics. In this talk, we review the necessary properties for effective filters and the difficulties in constructing useful filters for sharp gradients. As a basis for discussion, we utilize the Smoothness-Increasing Accuracy-Conserving (SIAC) filtering framework, which inherently takes advantage of the underlying physics and allows for the full resolution of the approximation and its derivatives in both the physical domain and Fourier signal space.
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