Dynamics of Civil Structures, Volume 2: Proceedings of the by Shamim Pakzad, Caicedo Juan

By Shamim Pakzad, Caicedo Juan

Dynamics of Civil buildings, quantity 2. complaints of the thirty fourth IMAC, A convention and Exposition on Dynamics of Multiphysical structures: From energetic fabrics to Vibroacoustics, 2016, the second one quantity of ten from the convention brings jointly contributions to this crucial zone of study and engineering. Th e assortment provides early fi ndings and case experiences on basic and utilized elements of Structural Dynamics, together with papers on:

• Modal Parameter Identifi cation

• Dynamic checking out of Civil Structures

• Human prompted Vibrations of Civil Structures

• version Updating

• Operational Modal Analysis

• harm Detection

• Bridge Dynamics

• Experimental ideas for Civil Structures

• Hybrid testing

• Vibration regulate of Civil Structures

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Additional info for Dynamics of Civil Structures, Volume 2: Proceedings of the 34th IMAC, A Conference and Exposition on Structural Dynamics 2016

Example text

The structure was instrumented with accelerometers to measure the ambient vibrations, while light detection and ranging (LiDAR) data was obtained to identify the locations and geometry of the major cracks. A finite element (FE) model of the damaged school building has been calibrated using typical values of material properties from Nepal [5, 6], and it has been validated though the comparison of the modal frequencies of the model with the identified frequencies obtained from the Natural Excitation Technique combined with Eigensystem Realization Algorithm (NExT-ERA), an operational modal analysis method.

If statistical models are fit to the structural responses at individual locations in the presence of missing observations, biased estimates may occur for the model parameters. Therefore, the purpose of a missing data analysis is to extract useful information about the underlying statistical model governing an incomplete dataset. The appropriate formulation of a missing data analysis is governed by the goals of the monitoring scheme. For example, Matarazzo and Pakzad use the expectation maximization (EM) algorithm in conjunction with the Kalman filter for system identification of bridges [16].

The efficiency of any sensor network is diminished with increasing sensor and setup costs, setup and collection times, network reliability, and power requirements [10]. For these reasons, the number of fixed sensors in a monitoring scheme M. N. edu © The Society for Experimental Mechanics, Inc. 2016 S. Pakzad, C. 1007/978-3-319-29751-4_4 23 24 M. N. Pakzad allowed by cost should be placed in optimal locations on a structure to avoid collection of more redundant data. However, to this end, optimal sensor locations may be inaccessible based on bridge geometries.

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