000019821 001__ 19821
000019821 005__ 20170118182338.0
000019821 04107 $$aeng
000019821 046__ $$k2017-01-09
000019821 100__ $$aConte, Joel P.
000019821 24500 $$aSeismic Structural Health Monitoring Using Bayesian Methods and Nonlinear Structural Finite Element Models

000019821 24630 $$n16.$$pProceedings of the 16th World Conference on Earthquake Engineering
000019821 260__ $$b
000019821 506__ $$arestricted
000019821 520__ $$2eng$$aThis paper presents an approach for structural health monitoring by integrating nonlinear structural finite element (FE) models and Bayesian methods. Batch and recursive Bayesian estimation methods are used to calibrate/update a nonlinear structural FE model of a structure (e.g., building, bridge, dam, etc.) employing the input-output dynamic data recorded during an earthquake event. Unknown parameters of the nonlinear FE model describing inertia, geometric, material constitutive models, and/or constraint properties of the structure are estimated using spatially-sparse response data recorded by homogeneous or heterogeneous sensor arrays. The updated nonlinear FE model is then used to assess the state of health or damage of the structure. The recursive Bayesian estimation method processes the measured data recursively, and updates the estimation of the FE model parameters progressively over the time history of the event. The recursive Bayesian estimation method results in a nonlinear Kalman filtering approach. The Extended Kalman filter (EKF) and Unscented Kalman filter (UKF) are employed as recursive Bayesian estimation methods. The batch estimation method is based on a maximum a posteriori estimation (MAP) approach, where the time history of the input and output measurements are used as a single batch of data for estimating the FE model parameters. This method results in a nonlinear optimization problem that is solved using a gradient-based optimization algorithm. For those estimation methods requiring the computation of structural FE response sensitivities with respect to the unknown FE model parameters, the direct differentiation method (DDM) is employed. Response data numerically simulated from a nonlinear FE model with unknown material model parameters of a five-story two-by-one bay reinforced concrete frame building subjected to bi-directional horizontal seismic excitation are used to illustrate the performance of the proposed framework.

000019821 540__ $$aText je chráněný podle autorského zákona č. 121/2000 Sb.
000019821 653__ $$aStructural health monitoring; Nonlinear finite element model; Bayesian methods; Damage identification; System identification

000019821 7112_ $$a16th World Conference on Earthquake Engineering$$cSantiago (CL)$$d2017-01-09 / 2017-01-13$$gWCEE16
000019821 720__ $$aConte, Joel P.$$iEbrahimian, Hamed$$iAstroza, Rodrigo
000019821 8560_ $$ffischerc@itam.cas.cz
000019821 8564_ $$s949995$$uhttps://invenio.itam.cas.cz/record/19821/files/4485.pdf$$yOriginal version of the author's contribution as presented on USB, paper 4485.
000019821 962__ $$r16048
000019821 980__ $$aPAPER