Optimization of Gaussian Random Fields
Name
Dow-2015-Optimization of Gaussian.pdf
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600.69 KB
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Adobe PDF
Checksum (MD5)
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Author(s)
Dow, Eric
Wang, Qiqi
Date Issued
July 2015
Journal
SIAM Journal on Scientific Computing
Publisher
Society for Industrial and Applied Mathematics
Citation
Dow, Eric, and Qiqi Wang. “Optimization of Gaussian Random Fields.” SIAM Journal on Scientific Computing 37, no. 4 (January 2015): A1685–A1704. © 2015, Society for Industrial and Applied Mathematics
Version
Final published version
Abstract
Many engineering systems are subject to spatially distributed uncertainty, i.e., uncertainty that can be modeled as a random field. Altering the mean or covariance of this uncertainty will, in general, change the statistical distribution of the system outputs. We present an approach for computing the sensitivity of the statistics of system outputs with respect to the parameters describing the mean and covariance of the distributed uncertainty. This sensitivity information is then incorporated into a gradient-based optimizer to optimize the structure of the distributed uncertainty to achieve desired output statistics. This framework is applied to perform variance optimization for a model problem and to optimize the manufacturing tolerances of a gas turbine compressor blade.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
Terms of Use
Article is made available in accordance with the publisher's policy and may be subject to US copyright law. Please refer to the publisher's site for terms of use.
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1137/140992187
