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Managing Uncertainty in Multiscale Systems via Simulation Model Refinement

[+] Author Affiliations
Ayan Sinha

Georgia Institute of Technology, Atlanta, GA

Jitesh H. Panchal

Washington State University, Pullman, WA

Janet K. Allen, Farrokh Mistree

University of Oklahoma, Norman, OK

Paper No. DETC2011-47655, pp. 471-483; 13 pages
doi:10.1115/DETC2011-47655
From:
  • ASME 2011 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 5: 37th Design Automation Conference, Parts A and B
  • Washington, DC, USA, August 28–31, 2011
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5482-2
  • Copyright © 2011 by ASME

abstract

The motivating question for this article is: ‘How should a system level designer allocate resources for auxiliary simulation model refinement while satisfying system level design objectives and ensuring robust process requirements in multiscale systems? Our approach consists of integrating: (i) a robust design method for multiscale systems (ii) an information economics based approach for quantifying the cost-benefit trade-off for mitigating uncertainty in simulation models. Specifically, the focus is on allocating resources for reducing model parameter uncertainty arising due to insufficient data from simulation models. A comprehensive multiscale design problem, the concurrent design of material and product is used for validation. The multiscale system is simulated with models at multiple length and time scales. The accuracy of the simulated performance is determined by the trade-off between computational cost for model refinement and the benefits of mitigated uncertainty from the refined models. System level designers can efficiently allocate resources for sequential simulation model refinement in multiscale systems using this approach.

Copyright © 2011 by ASME

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