Complementing Dynamical Equations with Data in Adaptive Reduced-Order Subspaces

Abstract

The proposed research aims at advancing the state of the art in the design of data driven reduced models for complex systems such as climate and atmospheric modeling, engineering turbulence and combustion models.

Document Details

Document Type
DoD Grant Award
Publication Date
Jul 15, 2016
Source ID
FA95501610231

Entities

People

  • Themistoklis Sapsis

Organizations

  • Air Force Office of Scientific Research
  • Harvard University
  • United States Air Force

Tags

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.
  • Computational Fluid Dynamics (CFD)
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers