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Title: Pareto optimal structural models and predictions consistent with data and modal residuals
Authors: Ntotsios, Evangelos
Christodoulou, Konstantinos
Papadimitriou, Costas
Issue Date: 2007
Publisher: © ASME
Citation: NTOTSIOS, E., CHRISTODOULOU, K. and PAPADIMITRIOU, C., 2007. Pareto optimal structural models and predictions consistent with data and modal residuals. IN: Proceedings of the ASME International Design Engineering Technical Conferences and Computers and Information in Engineering Conference (IDETC/CIE2007), Volume 1: 21st Biennial Conference on Mechanical Vibration and Noise, Parts A, B, and C, 4th-7th September 2007, Las Vegas, Nevada, pp. 1533 -1540
Abstract: A multi-objective identification method for model updating based on modal residuals is proposed. The method results in multiple Pareto optimal structural models that are consistent with the measured modal data, the class of models used to represent the structure and the modal residuals used to judge the closeness between the measured and model predicted modal data. The conventional single-objective weighted modal residuals method for model updating is also used to obtain Pareto optimal structural models by varying the values of the weights. Theoretical and computational issues related to the solution of the multi-objective and single optimization problems are addressed. The model updating methods are compared and their effectiveness is demonstrated using experimental results obtained from a three-story laboratory structure tested at a reference and a mass modified configuration. The variability of the Pareto optimal models and their associated response prediction variability are explored using two structural model classes, a simple 3-DOF model class and a higher fidelity 546-DOF finite element model class. It is shown that the Pareto optimal structural models and the corresponding response predictions may vary considerably. The variability of Pareto optimal structural model is affected by the size of modelling and measurement errors. This variability reduces as the fidelity of the selected model classes increases.
Description: This conference paper is closed access.
Version: Accepted for publication
DOI: 10.1115/DETC2007-35197
URI: https://dspace.lboro.ac.uk/2134/10778
Publisher Link: http://dx.doi.org/10.1115/DETC2007-35197
ISBN: 9780791848029
Appears in Collections:Closed Access (Civil and Building Engineering)

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