Data-Driven Mori-Zwanzig: Approaching a Reduced Order Model for Hypersonic Boundary Layer Transition
Michael Woodward, Yifeng Tian, Arvind Mohan, Yen Ting Lin, Christoph, Hader, Hermann Fasel, Misha Chertkov, and Daniel Livescu

TL;DR
This paper introduces a novel data-driven Mori-Zwanzig method for reduced-order modeling of hypersonic boundary layer transition, capturing unresolved dynamics through memory kernels and improving prediction accuracy.
Contribution
It applies a new data-driven Mori-Zwanzig algorithm to spatially inhomogeneous flows, extracting spatio-temporal structures and memory effects, advancing reduced-order modeling techniques.
Findings
Identifies spatio-temporal structures similar to DMD
Extracts hysteresis effects in memory kernels
Improves prediction accuracy over DMD
Abstract
In this work, we apply, for the first time to spatially inhomogeneous flows, a recently developed data-driven learning algorithm of Mori-Zwanzig (MZ) operators, which is based on a generalized Koopman's description of dynamical systems. The MZ formalism provides a mathematically exact procedure for constructing non-Markovian reduced-order models of resolved variables from high-dimensional dynamical systems, where the effects due to the unresolved dynamics are captured in the memory kernel and orthogonal dynamics. The algorithm developed in this work applies Mori's linear projection operator and an SVD based compression to the selection of the resolved variables (equivalently, a low rank approximation of the two time covariance matrices). We show that this MZ decomposition not only identifies the same spatio-temporal structures found by DMD, but it can also be used to extract…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsModel Reduction and Neural Networks · Fluid Dynamics and Turbulent Flows · Meteorological Phenomena and Simulations
