Compression and Assimilation for Resource-limited Operations

Abstract

This proposal describes the MIT contributions of a two-year collaborative research program between SRI International (SRI), the Nava l Research Laboratory (NRL) and the Massachusetts Institute of Technology (MIT) to enable effective use of ocean forecast data on fo rward operating platforms with limited communications and computing resources. The purpose of the effort is to mature and assess pro mising approaches to this problem for subsequent investment leading to transition of the developed capabilities to operations.Our MI T-MSEAS research will consists of four research thrusts involving reduced order modeling (ROM): i) decomposition of deterministic an d probabilistic forecasts for efficient compression, reduction and reconstruction; ii) machine learning for reduced-order modeling a nd forecasting; iii) adaptive and data-assimilative reduced-order modeling and forecasting; and iv) multi-resolution and multi-dynam ics ROMs.This abstract is approved for public release.

Document Details

Document Type
DoD Grant Award
Publication Date
Oct 22, 2021
Source ID
N000142112831

Entities

People

  • Pierre Felix Lermusiaux

Organizations

  • Massachusetts Institute of Technology
  • Office of Naval Research
  • United States Navy

Tags

Readers

  • Computational Fluid Dynamics (CFD)
  • Distributed Systems and Data Platform Development
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers

Technology Areas

  • AI & ML
  • AI & ML - DoD AI Strategy