A methodology to manage uncertainty during system-level conceptual design

Jay D. Martin, Timothy W. Simpson

Research output: Chapter in Book/Report/Conference proceedingConference contribution

13 Scopus citations

Abstract

Current design decisions must be made while considering uncertainty in both models and inputs to the design. In most cases this uncertainty is ignored in the hope that it is not important to the decision making process. This paper presents a methodology for managing uncertainty during system-level conceptual design of complex multidisciplinary systems. The methodology is based upon quantifying the information available in computationally expensive subsystem models with more computationally efficient kriging models. By using kriging models, the computational expense of a Monte Carlo simulation to assess the impact of the sources of uncertainty on system-level performance parameters becomes tractable. The use of a kriging model as an approximation to an original computer model introduces model uncertainty, which is included as part of the methodology. The methodology is demonstrated as a decision making tool for the design of a satellite system.

Original languageEnglish (US)
Title of host publicationProceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conferences - DETC2005
Subtitle of host publication31st Design Automation Conference
PublisherAmerican Society of Mechanical Engineers
Pages1183-1193
Number of pages11
ISBN (Print)079184739X, 9780791847398
DOIs
StatePublished - 2005
EventDETC2005: ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference - Long Beach, CA, United States
Duration: Sep 24 2005Sep 28 2005

Publication series

NameProceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference - DETC2005
Volume2 B

Other

OtherDETC2005: ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
Country/TerritoryUnited States
CityLong Beach, CA
Period9/24/059/28/05

All Science Journal Classification (ASJC) codes

  • General Engineering

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