The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Abstract Details
Activity Number:
|
106
|
Type:
|
Invited
|
Date/Time:
|
Monday, August 1, 2011 : 8:30 AM to 10:20 AM
|
Sponsor:
|
Section on Physical and Engineering Sciences
|
Abstract - #300029 |
Title:
|
Experiment Design and Optimization for Scenario Assessment Based on Computer Simulations
|
Author(s):
|
Brian Williams*+ and Christine Anderson-Cook and Leslie M. Moore and Jason Loeppky and Cetin Unal
|
Companies:
|
Los Alamos National Laboratory and Los Alamos National Laboratory and Los Alamos National Laboratory and University of British Columbia Okanagan and Los Alamos National Laboratory
|
Address:
|
, , ,
|
Keywords:
|
computer model ;
calibration ;
scenario assessment ;
experiment design ;
optimization ;
uncertainty quantification
|
Abstract:
|
We investigate experiment design and optimization strategies for scenario assessment with complex multi-physics codes. Component physics models (e.g. material strength, equation of state) contain uncertain parameters that are calibrated to experimental data. Other parameters allow for scenario definition, such as the geometry of the physical system or assumed operating conditions. We wish to identify regions of the scenario variable space in which at least one critical metric operates outside of its control bounds. Scenario assessment that properly accounts for uncertainty requires physics parameter uncertainty to be propagated through calculated performance metrics. It may be necessary to reduce this uncertainty through improved calibration of physics model parameters to expand the domain of acceptable scenario variation. Since we assume that multiple performance metrics will be utilized to determine the best new data to collect conditional on current understanding, we propose an approach that utilizes a comprehensive resource allocation framework that updates the current analysis and optimally reduces residual physics uncertainty and optimizes the regime of allowable scenarios.
|
The address information is for the authors that have a + after their name.
Authors who are presenting talks have a * after their name.
Back to the full JSM 2011 program
|
2011 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Continuing Education program, please contact the Education Department.