Improved numerical model for steel reinforcement corrosion in concrete considering influences of temperature and relative humidity Bo Yu a , Jianbo Liu a , Bing Li b,⇑ a Key Laboratory of Disaster Prevention and Structural Safety of Ministry of Education of China, School of Civil Engineering & Architecture, Guangxi University, Nanning 530004, China b School of Civil and Environmental Engineering, Nanyang Technological University, Singapore 639798, Singapore highlights  An improved numerical model for steel reinforcement corrosion in concrete was developed.  Influences of temperature and relative humidity on process control and corrosion rate were investigated.  Effects of forward and reverse electrode reactions on activation overpotential were considered.  Influence of temperature on the critical relative humidity under different conditions was discussed. article info Article history: Received 12 October 2016 Received in revised form 7 March 2017 Accepted 8 March 2017 Keywords: Concrete Steel reinforcement Corrosion rate Process control Temperature Relative humidity abstract An improved numerical model for steel reinforcement corrosion in concrete was developed to investigate the influences of temperature and relative humidity on process control and corrosion rate of steel rein- forcement in concrete. In order to overcome the limitations of current numerical corrosion models which oversimplify the activation overpotential, the influences of both forward and reverse electrode reactions on the activation overpotential were considered based on the original formulation of the Butler-Volmer equation. Meanwhile, the influences of temperature and relative humidity on the kinetic parameters of corrosion and the properties of concrete pore solution were considered simultaneously. Moreover, the applicability and efficiency of the proposed numerical model for steel reinforcement corrosion were ver- ified by comparing with current empirical prediction models as well as available experimental data of both artificially accelerated and natural exposure corrosion tests. Finally, the influences of temperature and relative humidity on process control and corrosion rate of steel reinforcement in concrete were investigated comprehensively. Furthermore, the influences of temperature, water-to-cement ratio, con- crete cover depth, and chloride content on the critical relative humidity were also discussed. Ó 2017 Elsevier Ltd. All rights reserved. 1. Introduction Corrosion of steel reinforcement in concrete has long been recognized as one of the major causes for durability deterioration of existing reinforced concrete (RC) structures [1–4]. It has been observed from experimental analysis that both temperature [5–7] and relative humidity [8,9] have significant effects on steel reinforcement corrosion in concrete. Hence, it is necessary to predict the corrosion rate of steel reinforcement in concrete under different environmental conditions (e.g., temperature and relative humidity) for service-life assessment and decision-making regarding the maintenance existing RC structures [10]. Based on the regression analysis of experimental data, various empirical prediction models [11–15] have been developed to establish the approximate relationships between corrosion rate of steel reinforcement and environmental or material parameters. According to the experimental data (2927 measurements) of 44 simulated bridge deck slabs over a 5-year exposure period, Liu and Weyers [11] proposed an empirical prediction model for corro- sion rate in terms of concrete chloride content, temperature, Ohmic resistance of concrete cover, and corrosion time. It is obvi- ous that this model ignores the influence of oxygen diffusion and concrete cover depth on corrosion rate of steel reinforcement. Vu and Stewart [12] developed an empirical prediction model of cor- rosion rate as the function of water-to-cement ratio, concrete cover depth, and corrosion time for a particular environmental condition with temperature of 20 °C and relative humidity of 75%. It should be noted that this model is based on the assumption that oxygen http://dx.doi.org/10.1016/j.conbuildmat.2017.03.045 0950-0618/Ó 2017 Elsevier Ltd. All rights reserved. ⇑ Corresponding author. E-mail addresses: gxuyubo@gxu.edu.cn (B. Yu), gxujianboliu@mail.gxu.cn (J. Liu), cbli@ntu.edu.sg (B. Li). Construction and Building Materials 142 (2017) 175–186 Contents lists available at ScienceDirect Construction and Building Materials journal homepage: www.elsevier.com/locate/conbuildmat