Journal article
A multiplicative regularized Gauss-Newton method with trust region Sequential Quadratic Programming for structural model updating
Mechanical systems and signal processing, v 131, pp 417-433
15 Sep 2019
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
The paper focuses on the development of an iterative minimization algorithm for structural identification. The algorithm consists of a Gauss-Newton method in which the ill-conditioning caused by noise pollution is mitigated by means of a multiplicative regularization technique used in conjunction with a bound constrained trust region method. Unlike the classic additive regularization technique, the amount of regularization is not determined a priori, but computed in an automatic fashion at each step of the iterative procedure. Specifically, the strength of the regularization is controlled by the norm of the model parameters weighted by a factor proportional to the current values of the least-square cost functional and the size of the trust region. The iterative procedure consists in solving a sequence of regularized local quadratic subproblems in a Sequential Quadratic Programming framework, for which a local convexity condition is given.
The proposed method is finally tested in the retrieval of the equivalent stiffness of the soil and bearings of a real, in-service bridge pier that was tested using experimental modal analysis. (C) 2019 Elsevier Ltd. All rights reserved.
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Details
- Title
- A multiplicative regularized Gauss-Newton method with trust region Sequential Quadratic Programming for structural model updating
- Creators
- Matteo Mazzotti - Drexel UniversityQiang Mao - Drexel UniversityIvan Bartoli - Drexel UniversityStylianos Livadiotis - Drexel University
- Publication Details
- Mechanical systems and signal processing, v 131, pp 417-433
- Publisher
- Elsevier
- Number of pages
- 17
- Grant note
- WVDH1426 / Pennoni Associates, Inc. WVDH1426 / West Virginia Department of Highways WVDH1426 / Federal Highway Administration
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Civil, Architectural, and Environmental Engineering
- Web of Science ID
- WOS:000487008600023
- Scopus ID
- 2-s2.0-85066766250
- Other Identifier
- 991019169814804721
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InCites Highlights
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- Web of Science research areas
- Engineering, Mechanical