Development of Theoretical Framework for Uncertainty-Based Design Problems

Abstract

The research objectives of the project revolve around the development of a rigorous mathematical framework for uncertainty-based design optimization, with an emphasis on the construction and analysis of a set of efficient numerical methods applicable for complex systems. The objectives include the following major components: 1. Constructing a mathematical framework, using generalized polynomial chaos (gPC) theory, to facilitate the analysis of uncertainty-based design optimization. 2. Developing novel and efficient numerical algorithms. 3. Conducting rigorous analysis and error estimates for the new algorithms. The work is performed on two kinds of uncertainty-based design optimization: * Robust design optimization, where the objective is to optimize the system performance while minimizing its sensitivity to uncertainty. * Reliability-based design optimization, where the objective is to optimize the system performance while keeping its failure probability under control.

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Document Details

Document Type
Technical Report
Publication Date
Feb 28, 2011
Accession Number
ADA563776

Entities

People

  • Dongbin Xiu

Organizations

  • Purdue University

Tags

DTIC Thesaurus Topics

  • Algorithms
  • Complex Systems
  • Computations
  • Differential Equations
  • Equations
  • Heuristic Methods
  • Mathematical Filters
  • Optimization
  • Partial Differential Equations
  • Polynomials
  • Probability
  • Probability Distributions
  • Random Variables
  • Reliability
  • Standards
  • Uncertainty
  • Universities

Fields of Study

  • Engineering

Readers

  • Adaptive Control and Estimation with Uncertainty in Dynamic Systems.