Technical Papers
Feb 25, 2016

Practical Nonlinear Modeling of Reinforced Concrete Structural Walls

Publication: Journal of Structural Engineering
Volume 142, Issue 12

Abstract

Current engineering practice typically relies on the use of fiber-based modeling approaches with uncoupled axial-bending (P-M) and shear (V) responses to simulate nonlinear behavior of reinforced concrete (RC) structural walls. However, more sophisticated numerical models are available that incorporate coupled P-M-V behavior. The effect of using uncoupled and coupled modeling approaches and the influence of various modeling assumptions, particularly modeling parameters related to wall shear behavior, on computed global and local building responses are reported. A five-story archetype RC wall-frame building designed according to current U.S. code provisions is used for the assessment. The results indicate that modeling parameters associated with wall shear behavior have a significant effect on computed responses for uncoupled models; use of commonly recommended effective shear stiffness of 0.2EcAw to account for effects of concrete cracking provides a reasonable estimate of roof displacement response. However, wall shear demands and interstory drift at stories where wall yielding occurs tend to be overestimated and underestimated, respectively, in comparison with results obtained using coupled wall models.

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Information & Authors

Information

Published In

Go to Journal of Structural Engineering
Journal of Structural Engineering
Volume 142Issue 12December 2016

History

Received: Apr 6, 2015
Accepted: Dec 10, 2015
Published online: Feb 25, 2016
Discussion open until: Jul 25, 2016
Published in print: Dec 1, 2016

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Authors

Affiliations

Kristijan Kolozvari, Ph.D., M.ASCE [email protected]
P.E.
Assistant Professor, Dept. of Civil and Environmental Engineering, California State Univ., Fullerton, CA 92831 (corresponding author). E-mail: [email protected]
John W. Wallace, Ph.D., M.ASCE [email protected]
P.E.
Professor, Dept. of Civil and Environmental Engineering, Univ. of California, Los Angeles, CA 90095-1593. E-mail: [email protected]

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