4 citations · 6 across the 6 of their papers we have counts for
4 papers · 1 filter
Data-Driven Mori-Zwanzig: Reduced Order Modeling of Sparse Sensors Measurements for Boundary Layer Transition
Michael Woodward, Yifeng Tian, Yen Ting Lin +5
Understanding, predicting and controlling laminar-turbulent boundary-layer transition is crucial for the next generation aircraft design. However, in real flight experiments, or wi…
Full trajectory optimizing operator inference for reduced-order modeling using differentiable programming
Surya Chakrabarti, Arvind T. Mohan, Datta V. Gaitonde +1
Accurate and inexpensive Reduced Order Models (ROMs) for forecasting turbulent flows can facilitate rapid design iterations and thus prove critical for predictive control in engine…
Data-Driven Mori-Zwanzig: Approaching a Reduced Order Model for Hypersonic Boundary Layer Transition
Michael Woodward, Yifeng Tian, Arvind Mohan +5
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…
Lagrangian Large Eddy Simulations via Physics Informed Machine Learning
Yifeng Tian, Michael Woodward, Mikhail Stepanov +4
High Reynolds Homogeneous Isotropic Turbulence is fully described within the Navier-Stokes (NS) equations, which are notoriously difficult to solve numerically. Engineers, interest…