Optimization and Uncertainty Quantification The Optimization and Uncertainty Quantification Capability in CCIM is focused on researching new algorithms and developing new software tools. We enable the application of these tools to optimize phenomena that are modeled by computer simulations, and to understand the uncertainties inherent within those phenomena. We have a broad base of academic, industrial, and labs collaborations. Our tools are used to solve problems of national importance for DOE, DOD, and DHS.

The initial design violated allowable response levels by a factor of 2, whereas the design optimized by DAKOTA removed all violations and still met strict weight targets.

Areas of Research:

• Continuous Optimization
  • DAKOTA - optimization and uncertainty quantification toolkit
    (Contact: Michael S. Eldred)
  • Design Optimization Applications
    (Contacts: Anthony A. Giunta and Bart van Bloemen Waanders)
  • PDE-Constrained Optimization - sensitivity formulations, intrusive optimization
    (Contacts: Bart van Bloemen Waanders, Roscoe Bartlett and S. Scott Collis)
  • Surrogate-Based Optimization Algorithms
    (Contacts: Anthony A. Giunta and Michael S. Eldred)
  • Transient Optimization
    (Contact: S. Scott Collis)
• Uncertainty Estimation
  • Sampling and Statistical Understanding
    (Contacts: Laura P. Swiler and Anthony A. Giunta)
  • Uncertainty Quantification and Optimization Under Uncertainty - software tools
    (Contact: Michael S. Eldred and Anthony A. Giunta)
  • Validation and Verification - methodologies, validation metrics
    (Contact: Timothy G. Trucano)
• Homeland Security R&D
  • Air and Water Security - event inversion and control algorithms
    (Contacts: Bart van Bloemen Waanders and Cynthia A. Phillips)

Program Contact: James R. Stewart

 
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Modified on: May 6, 2008