In a chloride environment, taking reinforced concrete structures as the research object, the corrosion rate of reinforcement determines its corrosion expansion because multiple coupling parameters will affect the corrosion rate of reinforcement, which is extremely difficult to effectively predict. In this paper, 144 sets of experimental data were collected and sorted out by reading the relevant literature, and six empirical models for predicting the corrosion rate of steel bars were compared and analyzed based on these experimental data. Based on the investigations, a new empirical model is proposed for predicting the corrosion rate of reinforcement, and the relevant influencing factors are considered in the new model. By comparing the 144 sets of experimental data and 90 experimental data for this paper, the new prediction model can well predict the corrosion rate of reinforcement. Furthermore, the time variability of the new prediction model is verified. The probability distribution characteristics of seven prediction models are obtained through model error analysis, which provides a theoretical basis for the next step of concrete cover cracking and reliability analysis.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.