A Framework for Quantifying Uncertainty in InfoSymbiotic Systems Arising in Atmospheric Environments

Abstract

This project is aimed to develop new fast algorithms and a rigorous framework for quantifying, controlling and reducing uncertainty and their effect on model and data errors, in environments such as DDDAS where data area dynamically incorporated into models and the models in reverse collect additional data and in targeted ways to improve the model.

Document Details

Document Type
DoD Grant Award
Publication Date
Feb 06, 2017
Source ID
FA95501710015

Entities

People

  • Adrian Sandu

Organizations

  • Air Force Office of Scientific Research
  • United States Air Force
  • Virginia Tech

Tags

Fields of Study

  • Environmental science

Readers

  • Distributed Systems and Data Platform Development
  • Ocean-Atmosphere Mesoscale Modeling, Data Assimilation, and Flux Boundary Layers
  • Team-Based Human-Centered Cognitive Task Decision Making and Information Performance.