Abstract
The importance of sensitivity analysis in engineering design cannot be over-emphasized. In design under uncertainty, sensitivity analysis is performed with respect to the probabilistic characteristics. Global sensitivity analysis (GSA), in particular, is used to study the impact of variations in input variables on the variation of a model output. One of the most challenging issues for GSA is the intensive computational demand for assessing the impact of probabilistic variations. Existing variance-based GSA methods are developed for general functional relationships but require a large number of samples. In this work, we develop an efficient and accurate approach to GSA that employs analytic formulations derived from metamodels of engineering simulation models. We examine the types of GSA needed for design under uncertainty and derive generalized analytical formulations of GSA based on a variety of metamodels commonly used in engineering applications. The benefits of our proposed techniques are demonstrated and verified through both illustrative mathematical examples and the robust design for improving vehicle handling performance. global sensitivity analysis, metamodeling, simulation-.
Original language | English (US) |
---|---|
Pages | 953-962 |
Number of pages | 10 |
State | Published - Dec 1 2004 |
Event | 2004 ASME Design Engineering Technical Conferences and Computers and Information in Engineering Conference - Salt Lake City, UT, United States Duration: Sep 28 2004 → Oct 2 2004 |
Other
Other | 2004 ASME Design Engineering Technical Conferences and Computers and Information in Engineering Conference |
---|---|
Country | United States |
City | Salt Lake City, UT |
Period | 9/28/04 → 10/2/04 |
Keywords
- Analytical formulation
- Based design
- Tensor basis product function
- Uncertainty
ASJC Scopus subject areas
- Modeling and Simulation
- Mechanical Engineering
- Computer Science Applications
- Computer Graphics and Computer-Aided Design