Development of Accurate Damping Models for Nonlinear Time History Analysis
-
2019-08-14
Details
-
Creators:
-
Corporate Creators:
-
Corporate Contributors:
-
Subject/TRT Terms:
-
Publication/ Report Number:
-
Resource Type:
-
Geographical Coverage:
-
Edition:Final Report 07/27/2017-05/31/2019
-
Corporate Publisher:
-
Abstract:California’s bridges provide vital transportation links, and their seismic performance impacts the entire state and thus, the nation. In order to accurately estimate the response of bridges under earthquake ground motions, highly detailed and accurate Finite Element (FE) models are necessary. While the nonlinear behaviors of most elements can be captured relatively well with current capabilities, devising accurate models and parameter values for damping has eluded researchers and practitioners alike. In order to identify the inherent damping from real-life data and distinguish its effects from other sources of energy dissipation, a novel Bayesian Finite Element (FE) model updating framework was developed and extensively verified and validated through synthetic and real-life data. This new method can be applied to real-life earthquake data recorded by bridges which are instrumented by Caltrans through the California Strong Motion Instrumentation Program (CSMIP). Two typical concrete bridges in California were selected and the proposed solution was applied to several earthquake data sets. It was determined that the identified inherent damping confirms that the current 5% Rayleigh damping model is only reliable if the bridge is under a moderate earthquake. If the level of excitation is weak, 2% damping is advised. As no strong earthquake data has been recorded by these two bridges, it was not possible to present any validated conclusion for this level of earthquake intensity. The methodology developed herein has no limitations in this regard and can be applied to other bridges and intensity levels in the future.
-
Format:
-
Funding:
-
Collection(s):
-
Main Document Checksum:urn:sha256:e6b8c487a9de056bd964ca350c12659839ff463cce2a9de5c07ee0a5fe96527d
-
Download URL:
-
File Type: