Bayesian Nonlinear Finite Element Model Updating of a Full-Scale Bridge-Column Using Sequential Monte Carlo

Mukesh K. Ramancha*, Rodrigo Astroza, Joel P. Conte, Jose I. Restrepo, Michael D. Todd

*Autor correspondiente de este trabajo

Resultado de la investigación: Capítulo del libro/informe/acta de congresoContribución a la conferenciarevisión exhaustiva

5 Citas (Scopus)

Resumen

Digital twin-based approaches for structural health monitoring (SHM) and damage prognosis (DP) are emerging as a powerful framework for intelligent maintenance of civil structures and infrastructure systems. Model updating of nonlinear mechanics-based Finite Element (FE) models using input and output measurement data with advanced Bayesian inference methods is an effective way of constructing a digital twin. In this regard, the nonlinear FE model updating of a full-scale reinforced-concrete bridge column subjected to seismic excitations applied by a large shake table is considered in this paper. This bridge column, designed according to US seismic design provisions, was tested on the NEES@UCSD Large High-Performance Outdoor Shake Table (LHPOST). The column was subjected to a sequence of ten recorded earthquake ground motions and was densely instrumented with an array of 278 sensors consisting of strain gauges, linear and string potentiometers, accelerometers and Global Positioning System (GPS) based displacement sensors to measure local and global responses during testing. This heterogeneous dataset is used to estimate/update the material and damping parameters of the developed mechanics-based distributed plasticity FE model of the bridge column. The sequential Monte Carlo (SMC) method (set of advanced simulation-based Bayesian inference methods) is used herein for the model updating process. The inherent architecture of SMC methods allows for parallel model evaluations, which is ideal for updating computationally expensive models. © 2020, The Society for Experimental Mechanics, Inc.
Idioma originalInglés
Título de la publicación alojadaModel Validation and Uncertainty Quantification, Volume 3 - Proceedings of the 38th IMAC, A Conference and Exposition on Structural Dynamics, 2020
EditoresZhu Mao
EditorialSpringer
Páginas389-397
Número de páginas9
ISBN (versión impresa)9783030487782
DOI
EstadoPublicada - 2020
Evento38th IMAC, A Conference and Exposition on Structural Dynamics, 2020 - Houston, Estados Unidos
Duración: 10 feb. 202013 feb. 2020

Serie de la publicación

NombreConference Proceedings of the Society for Experimental Mechanics Series
ISSN (versión impresa)2191-5644
ISSN (versión digital)2191-5652

Conferencia

Conferencia38th IMAC, A Conference and Exposition on Structural Dynamics, 2020
País/TerritorioEstados Unidos
CiudadHouston
Período10/02/2013/02/20

Nota bibliográfica

Publisher Copyright:
© 2020, The Society for Experimental Mechanics, Inc.

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