Statistical Approach to Modeling Reduced Shear Capacity of Corrosion-Damaged Reinforced Concrete Beams
Publication: Practice Periodical on Structural Design and Construction
Volume 26, Issue 2
Abstract
In the 2017, ASCE graded the national infrastructure of the United States as D+ overall. The ASCE gave the national School Buildings category a D+ grade and the Bridges category a C+ grade. Steel corrosion is the main reason for the trend toward deterioration in US infrastructure, including buildings, bridges, pipelines, and wharves. Reinforced concrete (RC) is among the most widely used primary construction materials worldwide. Objectives of the current research were to determine the design parameters that have the greatest impact on the reduced shear capacity of RC beams in the presence of corrosion, and to create a model to estimate the reduced shear capacity by refining the ACI shear design model for RC beams in buildings. Using a database of experimental tests, an artificial neural network model was created to estimate reduced shear strength and to perform a sensitivity analysis of the parameters affecting residual shear capacity. The sensitivity analysis showed that the compressive strength of concrete is the most influential parameter affecting reduced shear strength. A multiple linear-regression analysis was also performed to aid in proposing a new model.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
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Published In
Practice Periodical on Structural Design and Construction
Volume 26 • Issue 2 • May 2021
Copyright
© 2020 American Society of Civil Engineers.
History
Received: Jun 15, 2020
Accepted: Oct 22, 2020
Published online: Dec 24, 2020
Published in print: May 1, 2021
Discussion open until: May 24, 2021
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