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Uncertainty in the Seismic Response of Structural Components due to Material Variability
Published
Author(s)
Christopher L. Segura, Siamak Sattar
Abstract
Inherent variability in the mechanical properties of reinforcing steel and concrete introduces uncertainty into the seismic assessment of reinforced concrete structures. To quantify the impact of material uncertainty, one-hundred variations of a numerical model of a reinforced concrete structure are evaluated for their seismic performance at several earthquake shaking intensity levels. The one-hundred models differ only by the constitutive parameters used to model the materials, which are selected in accordance with measured statistical distributions of the mechanical properties of reinforcing steel bars and concrete. Material property statistical distributions, and correlations between material properties, are established using test data collected by the authors and test data available in the scientific literature. Preliminary results from evaluations at the component level (i.e., individual column) indicate that dispersion in the predicted drift response for a given ground shaking intensity (Sa[T1]) generally increases with shaking intensity, especially in the post-peak response regime. Of particular interest is the fact that relatively large dispersion values (coefficient of variation, COV, up to 20%) are obtained for ground shaking intensities that produce only moderate ductility demands, prior to the onset of strength loss. Larger dispersion in the post- peak regime can be attributed to greater uncertainties in the material response of concrete as material softening occurs. Evaluations at the system level (i.e., frame system) are currently ongoing and will be available at the time of the presentation.
Proceedings Title
Proceedings of the 17th World Conference on Earthquake Engineering
Segura, C.
and Sattar, S.
(2020),
Uncertainty in the Seismic Response of Structural Components due to Material Variability, Proceedings of the 17th World Conference on Earthquake Engineering, Sendai, -1, [online], https://tsapps.nist.gov/publication/get_pdf.cfm?pub_id=929562
(Accessed December 6, 2024)