Complementing Dynamical Equations with Data in Adaptive Reduced-Order Subspaces

reportActive / Technical Report | Accesssion Number: AD1146065 | Open PDF

Abstract:

This was a no-cost extension with limited annual budget, corresponding to 3 months of postdoc support. Overt this period we worked on finalizing several manuscripts on optimal sampling for the prediction and quantification of extreme events. A review article on extremes in fluids and waves was submitted and published to the Annual Review of Fluid Mechanics, during this period.

Author(s):
Sapsis, Themistoklis
Author Organization(s):
MASSACHUSETTS INSTITUTE OF TECHNOLOGY
Funding Organization(s):
Air Force Office of Scientific Research, ARLINGTON , VA
Document Type:
Technical Report/Final Report
Publication Date:
2021 Aug 17
Pagination:
13

Security Markings

DOCUMENT & CONTEXTUAL SUMMARY

Distribution Code:
A - Approved For Public Release
Distribution Statement: Public Release

RECORD

Collection: TRECMS
Identifying Numbers
Report Number(s):
AFRL-AFOSR-VA-TR-2021-0105
Grant Number(s):
FA9550-16-1-0231
Program Element Number(s):
PE61102F
Subject Terms
Modernization Areas:
AI and Machine Learning
Communities of Interest:
Energy and Power Technologies
Descriptor(s):
neural networks, computational science, fluid flow, computational fluid dynamics, control systems, engineering, equations, fluid mechanics, information science, machine learning, scientific research, variational equations, algorithms, eigenvalues, flow, fluid dynamics, physics laboratories
Keyword(s):
dynamical equations, adaptive reduced-order subspaces, otd (optimally time-dependent), otd modes, orthonormal tangent vectors, extreme transient events, Control of instabilitity
Subject Categories:
Mathematical and Computer Sciences
Creation Date:
2021 Aug 26
Update Date:
2021 Nov 19