Objectives

The goal of the M3 MURI project is to create and investigate principled approaches to analysis and decision-making for multi-physics systems that explicitly integrate the breadth of available information sources.

The project has five overall research objectives:

  1. Develop statistical approaches for defining and quantifying fidelity
  2. Establish decision-theoretic methods for optimally managing sources of uncertain multi-physics information
  3. Create reduced models with goal-driven adaptation to multi-physics interactions and with quantified uncertainty
  4. Formulate an information-theoretic approach for handling multi-physics coupling
  5. Create a scalable framework for solving multi-physics analysis and design problems under uncertainty

A multidisciplinary project

M3 research leverages the mathematical foundations and methods of information theory, decision theory, and machine learning, and brings these elements together in new ways with multidisciplinary design optimization (MDO), multifidelity optimization, uncertainty quantification (UQ), and reduced modeling.

M3 research involves crosscutting research themes of:

(de)composition

statistical learning

exploiting structure

goal-driven uncertainty management

scalable methods

Overview

M3 research is organized under three integrated research thrusts:

RT1: Optimal information-source management

RT2: Goal-oriented reduced models for the multi-source multi-physics setting

RT3: Managing coupling in multi-physics systems

Integration of the 3 research thrusts