Computational Methods for Data-Driven and Reduced-Order Modeling of Multiscale Physics
Abstract
Multi-resolution DMD is a critically enabling algorithm which allows for the data-driven construction of ROMs at each level of temporal activity. Data-driven models can be inferred through a number of techniques, including DMD, Koopman theory and sparse identification of nonlinear dynamics. And importantly, the innovation of DMD with control can be used to connect ROMs at different temporal scales. Specifically, fast scales act as input for slow scales and vice-versa. Thus the mathematical architecture allows for the construction of heterogeneous, multi-scale ROMs, each of which acts as an input to the other levels. The quality and appropriateness of the multi-scale models can be evaluated through information theory criteria, providing a robust cross-validation of the inferred ROMs.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Sep 11, 2017
- Source ID
- FA95501710329
Entities
People
- J. Nathan Kutz
Organizations
- Air Force Office of Scientific Research
- United States Air Force
- University of Washington