Data-Driven Mori-Zwanzig: Reduced Order Modeling of Sparse Sensor Measurements for Boundary Layer Transition
- Los Alamos National Laboratory
- The University of Arizona
- Research Organization:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Organization:
- USDOE Laboratory Directed Research and Development (LDRD) Program
- DOE Contract Number:
- 89233218CNA000001
- OSTI ID:
- 1990083
- Report Number(s):
- LA-UR-23-27814
- Resource Relation:
- Conference: AIAA Aviation and Aeronautics Forum and Exposition ; 2023-06-12 - 2023-06-16 ;
- Country of Publication:
- United States
- Language:
- English
Similar Records
From Koopman to Mori-Zwanzig for Data-Driven Modeling of Dynamical Systems
Data-Driven Learning for the Mori--Zwanzig Formalism: A Generalization of the Koopman Learning Framework
Data-driven learning of Mori–Zwanzig operators for isotropic turbulence
Conference
·
2023
·
OSTI ID:2202614
Data-Driven Learning for the Mori--Zwanzig Formalism: A Generalization of the Koopman Learning Framework
Journal Article
·
2021
· SIAM Journal on Applied Dynamical Systems
·
OSTI ID:1872339
+1 more
Data-driven learning of Mori–Zwanzig operators for isotropic turbulence
Journal Article
·
2021
· Physics of Fluids
·
OSTI ID:1874192
+1 more