Title: A Statistical Approach to Modeling the Reduced Flexural Capacity of Corrosion-Damaged Reinforced Concrete Beams
Author(s): Mahmoodreza Soltani, Ali AlilooeeDolatabad, Eugenia Akurang, and Adham Abu-Abaileh
Publication: Structural Journal
Appears on pages(s): 175-182
Keywords: database analysis; multiple linear regression analysis; reinforcement mass loss ratio; sensitivity analysis
The ASCE 2017 Report Card reported the national grade for U.S. infrastructure as a D+ in the overall category, a D+ for the School Buildings category, and a C+ for the Bridges category. Steel corrosion is one of the main reasons for the trend of deterioration in U.S. infrastructure. Reinforced concrete (RC) is used as the primary construction material worldwide. Objectives for this study were to determine the design parameters that have the most significant impact on the reduced flexural strength of RC beams in the presence of corrosion and to create a model to estimate the reduced flexural strength through refining the ACI 318-19 flexural design model. Using an experimental database of 410 tests, a linear model was created to estimate the reduced flexural strength and to perform a sensitivity analysis of the parameters affecting the residual flexural strength. The sensitivity analysis showed that the effective depth of reinforcement (d) and the tensile longitudinal reinforcement force (Asefy) are the most influential parameters affecting the reduced flexural strength. A multiple linear regression analysis was also performed to propose a new model by incorporating the two most significant parameters that inversely affect the reduced flexural strength of corrosion-damaged RC beams.