Regularization in Model Updating
B Titurus & MI Friswell (University of Bristol)
International Journal for Numerical Methods in Engineering, Vol. 75, No. 4, July 2008, pp. 440-478
This paper presents the theory of sensitivity-based model updating with a special focus on the properties of the solution that result from the combination of optimization of the response prediction with a priori information about the uncertain parameters. Model updating, together with the additional regularization criterion, is an optimization with two objective functions, and must be linearized to obtain the solution. Structured solutions are obtained, based on the generalized singular value decomposition (GSVD), and specific features of the parameter and response paths as the regularization parameter varies are explored. The four different types of spaces that arise in the solution are discussed together with the characteristics of the regularized solution families. These concepts are demonstrated on a simulated discrete example and on an experimental case study.
This material has been published in the International Journal for Numerical Methods in Engineering, Vol. 75, No. 4, July 2008, pp. 440-478. Unfortunately the copyright agreement with Wiley InterScience does not allow for the PDF file of the paper to be available on this website. However the paper is available from the Wiley website - see the link below.
Link to paper using doi:10.1002/nme.2257
International Journal for Numerical Methods in Engineering on Wiley InterScience