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Selecting an Appropriate Metamodel: The Case for NURBs Metamodels

[+] Author Affiliations
Cameron J. Turner

Los Alamos National Laboratory, Los Alamos, NM

Richard H. Crawford

University of Texas at Austin, Austin, TX

Paper No. DETC2005-85043, pp. 759-771; 13 pages
  • ASME 2005 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 2: 31st Design Automation Conference, Parts A and B
  • Long Beach, California, USA, September 24–28, 2005
  • Conference Sponsors: Design Engineering Division and Computers and Information in Engineering Division
  • ISBN: 0-7918-4739-X | eISBN: 0-7918-3766-1
  • Copyright © 2005 by ASME


Metamodels are becoming increasingly popular for representing unknown black box functions. Several metamodel classes exist, including response surfaces and spline-based models, kriging and radial basis function models, and neural networks. For an inexperienced user, selecting an appropriate metamodel is difficult due to a limited understanding of the advantages and disadvantages of each metamodel type. This paper reviews several major metamodeling techniques with respect to their advantages and disadvantages and compares several significant metamodel types for use as a black box metamodeling tool. The results make a strong case for using Non-Uniform Rational B-spline (NURBs) HyPerModels as a generic metamodeling tool.

Copyright © 2005 by ASME



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