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Civil-Comp Conferences
ISSN 2753-3239
CCC: 3
PROCEEDINGS OF THE FOURTEENTH INTERNATIONAL CONFERENCE ON COMPUTATIONAL STRUCTURES TECHNOLOGY
Edited by: B.H.V. Topping and J. Kruis
Paper 10.2

A Recursive Model Updating Algorithm for Multi-element Hybrid Simulation of Structures

F. Mokhtari and A. Imanpour

Department of Civil and Environmental Engineering, University of Alberta, Edmonton, Alberta, Canada

Full Bibliographic Reference for this paper
F. Mokhtari, A. Imanpour, "A Recursive Model Updating Algorithm for Multi-element Hybrid Simulation of Structures", in B.H.V. Topping, J. Kruis, (Editors), "Proceedings of the Fourteenth International Conference on Computational Structures Technology", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 3, Paper 10.2, 2022, doi:10.4203/ccc.3.10.2
Keywords: hybrid simulation, model updating, data-driven simulation, machine learning, dynamics of structures, substructuring, system identification.

Abstract
Hybrid simulation is a cost-effective method of testing structures under seismic loading that combines numerical and experimental methods through partitioning the structure into; 1) numerical substructure simulating the well-understood components of the structure, and 2) physical substructure representing the critical components of the structure. The hybrid simulation results can become biased and uncertain when only one or a limited number of potential critical components, e.g., seismic fuses, are physically tested due to laboratory or cost constraints. Furthermore, the critical components modelled in the numerical substructure are often calibrated using experimental test results of similar prototype specimens under a predefined loading protocol, which fails to consider the effects of dynamic loading characteristics to which it will be subjected in hybrid simulation. This paper proposes a new recursive model updating algorithm incorporated into the conventional seismic hybrid simulation framework to leverage the data collected in real-time from the physical specimen of one of the critical elements and integrate a new data-driven model into the numerical substructure. The data-driven model, which is being progressively updated owing to the proposed model updating algorithm, is responsible for predicting the nonlinear cyclic response of the other critical components of the system that are not physically tested. To develop the data-driven model, the parameters of the Prandtl-Ishlinskii model are first estimated using a sparse regression algorithm and then updated during the hybrid simulation using the recursive least-squares algorithm. The simulation accuracy of the model updating algorithm is assessed through nonlinear response history analysis of a two-storey steel buckling-restrained braced frame, which consists of a virtual experimental specimen (first-storey brace) and the model updating algorithm integrated into the numerical model of the structure to predict the second-storey brace force. The results suggest that the application of the model updating algorithm in conventional seismic hybrid simulation yields a more accurate and create an unbiased seismic simulation tool that can be used to examine the seismic response of multi-storey structural systems.

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