Research Area: | Research Publication | Year: | 1999 | ||
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Type of Publication: | Technical Report | Keywords: | Response Surface Methodology, Approximation Methods, Kriging, Design of Experiments | ||
Authors: | Srivastava, Amit; Hacker, Kurt; Lewis, Kemper; Simpson, Timothy | ||||
Abstract: | In the present world of advancing technology, designers are faced with designing
increasingly complex engineering systems. Despite a steady increase in computing
power, the complexity of these engineering analyses seems to advance at the same rate.
In addition, the design of complex engineering systems involves the integration of
multiple disciplines and the resolution of conflicting objectives. Traditional parametric
design analysis is inadequate to analyze these large-scale systems because of its
computational inefficiency; therefore, a departure from the traditional parametric design
approach is required. Approximation techniques may be applied to build computationally
inexpensive surrogate models for large-scale systems to replace expensive-to-run
computer analysis codes. Response surface models are frequently utilized to construct
surrogate approximations; however, they may be inefficient for systems having with a
large number of design variables. Kriging, an alternative method for creating surrogate
models, is applied in this work to construct approximations of computationally expensive
computer analyses for a large-scale system. Comparisons between response surfaces and
kriging are made based on the results of a case study, the High Speed Civil Transport
(HSCT) approximation challenge. In this problem, 2490 analysis points are already
generated, and the challenge is to choose 500 or fewer and construct an accurate
approximation. Since the analysis points are already chosen, a modified design of
experiments technique is needed to select the appropriate sample points. In this paper, a
number of approaches to handling this problem are presented, and the results are
compared against previous work |
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Comments: | International Journal for Product and Process Improvement |
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Full text: askh_2000.pdf
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