Environmental conditions, variability in building material, and fabrication error are several contributors that shorten a structure’s service life. While infrastructure might not have visible exterior damage, there is always the risk for failure due to internal or obscured damage. There has been growing research in the area of Nondestructive testing. However, these methods often disregard uncertainties in the construction and maintenance processes. Nevertheless, providing an accurate and robust method for detecting, localizing, and estimating the severity of existing damage relies on parameterizing uncertainties surrounding material properties, composition, and loading history. This work combines conventional physics-based modeling with data-driven search strategies to infer unobservable information about the structure. The proposed approach uses Finite Element Analysis with automated adjoint calculation to efficiently obtain gradients in the solution with respect to the model parameters. The hybrid model updates the postulated material properties to match the mechanical compliance of a simulated structure with observations from a reference structure. Here we use a simple cantilever beam model to study and evaluate the effectiveness of the proposed approach. In addition, we analyze the results from multiple search strategies used to obtain the mechanical properties. We find that the benefit in search efficiency gained from the analytical evaluation of the gradients is offset by the additional computational cost of adjoint simulation compared to gradient-free search. However, we expect that the benefit of adjoint simulation would be more pronounced in problems with more degrees of freedom.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.