Chloride diffusion models for plain and blended cement concretes exposed to laboratory and atmospheric marine conditions

• Published in: Journal of materials research and technology 2022-03, Vol.17, p.125-138
• Main Authors: Al-Sodani, Khaled A.Alawi, Al-Zahrani, Mesfer Mohammad, Maslehuddin, Mohammed, Al-Amoudi, Omar S.Baghabra, Al-Dulaijan, Salah U.
• Format: Article
• Language: English
• Subjects: Chloride diffusion; Correlation models; Laboratory assessment; Marine exposure; Plain and blended cement concrete
• ISSN: 2238-7854
• DOI: 10.1016/j.jmrt.2021.12.136

Chloride-induced corrosion of steel in a reinforced concrete structure compromises its safety and may decrease the designed service-life. The initiation and the rate of reinforcement corrosion mainly depends on the diffusion of chloride ions to the surface of the steel bars. As such, it is important to determine the coefficient of apparent chloride diffusion (Da) for the type of concrete to be used in a structure, which is time-consuming. Therefore, the development of a short-term and simple procedure to predict Da is highly desirable. This study was conducted to develop a correlation between the short-term chloride migration coefficient (Dnssm) and long-term Da for Type I, Type V and pozzolanic cement concretes. Two groups of concrete specimens, each consisting of five concrete mixtures designed with a w/b ratio of 0.4, were prepared. The first group was exposed to a marine exposure site for 10 years and Da was evaluated after 1, 2, 5 and 10 years. The second group was tested according to NT BUILD 492 under laboratory conditions to determine the short-term Dnssm. Correlation models between the field and laboratory results were developed and statistically validated by comparing the predicted values with the measured ones. The predicted Da values are within ±7% of the measured values. Further, the Dnssm of pozzolanic cement concretes is 2.20–4.40 and 3.55 to 7.30 times less than that of Type I and Type V cement concretes, respectively. The developed models can be utilized to assess the long-term Da by determining the short-term Dnssm.