New Degradation Models Based on Pre-Cracked Bridge Deck Rebars to Better Address Infrastructure Corrosion

In this webinar, Professor David W. Coit presents a new reliability model based on a two-stage gamma process model, developed for steel rebar corrosion under accelerated conditions. Deterioration of concrete structures is a major concern and corrosion of steel reinforcement is among the major causes. The corrosion process aggressiveness increases with the existence of cracks that facilitates the transfer of chloride and accelerates the steel erosion and that affects the structure’s service life negatively. The Rutgers Infrastructure Monitoring and Evaluation (RIME) Group, led by Prof. Hani Nassif, has conducted extensive testing of steel rebars in concrete test samples. In Professor Coit’s study, the corrosion rate of four major types of embedded steel rebars is being investigated through the accelerated corrosion testing. To simulate the service environment expected in bridges, the specimens were pre-cracked and subjected to diluted and concentrated chloride solutions. The testing program took into consideration two common types of concrete (Class A & high performance concrete), four cracking patterns and two chloride concentrations (3% and 15%). The cracking patterns combine two crack widths (0.011 inch and 0.035 inch) and two crack depths (0.5 inch and inch). After collecting data for three years, a two-stage degradation model was applied to understand and analyze the corrosion process for the fours rebars under the different conditions presented. The testing time of pre-cracking samples was mathematically translated for uncracked bridge rebar evaluation. The results obtained in this paper demonstrated the effectiveness of pre-cracking-induced concrete on performing accelerated corrosion testing.

David W. Coit is a Professor in the Department of Industrial & Systems Engineering at Rutgers University, Piscataway, NJ, USA. His current teaching and research involves system reliability modeling and optimization, data analysis and forecasting and energy systems optimization. His research has been funded by National Science Foundation (NSF), U.S. Army, U.S. Navy, industry, and power utilities. He has over 120 published journal papers and over 90 peer-reviewed conference papers. He has been awarded several NSF grants, including a CAREER grant from NSF to develop new reliability optimization algorithms considering uncertainty. He was also the recipient of the P. K. McElroy award, Alain O. Plait award and William A. J. Golomski award for best papers and tutorials at the Reliability and Maintainability Symposium (RAMS). He also has over ten years of experience working for IIT Research Institute (IITRI), Rome NY. He received a BS degree in mechanical engineering from Cornell University, an MBA from Rensselaer Polytechnic Institute, and MS and PhD in industrial engineering from the University of Pittsburgh. He is a Department Editor for IISE Transactions and an Associate Editor for IEEE Transactions on Reliability and Journal of Risk and Reliability, and he is a member of IIE and INFORMS.

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