Abstract

We discuss several simulation technologies that have enabled science applications to resolve physical features and processes at unprecedented scales. This in turn has enabled highly-precise reduced-order models that can be used for control and optimization, targeting real-time applications. The first technology, adaptive mesh refinement, enables highly-accurate, fast solutions for localized or intermittent phenomena, although it greatly complicates software. The second breakthrough has been higher-order numerical accuracy in space and time, even in complex and moving geometries, without requiring complex mesh generation. Not only do these approaches reduce simulation error more rapidly, but they better match physical theory and can even provide error sensitivity and reduced-order models at coarse resolutions, if properly designed. The third has been the incredible increase in computational science capability from community software investments, which have adapted to HPC hardware trends to enable massively parallel, high-performance science codes. We will show some multi-scale, multi-physics results that use all three, and can help identify cheaper physical models that, with careful assessment, enable design optimization and real-time control.

Video Recording