Estimation of internal corrosion degree from observed surface cracking of concrete using mesoscale simulation with Model Predictive Control

Abstract

AbstractCorrosion of the steel reinforcing bars in concrete structures is one of the major maintenance problems. Corrosion results in expansive pressure on the surrounding concrete, which causes internal damage that may become visible as surface cracking. Such damage may degrade structural safety and serviceability. Effective maintenance requires the evaluation of residual performance based on estimates of spatially nonuniform levels of corrosion, which are typically obtained through surface measurements only. In this study, the authors have developed a simulation system for estimating the levels of internal corrosion along the reinforcing bar length from surface crack information. This innovative system is produced by integrating the technique of Model Predictive Control (MPC) with Rigid‐Body‐Spring Models (RBSM) of corrosion‐induced cracking at the concrete mesoscale. In this study, MPC controls the simulated surface cracks such that they match the observed cracks by optimizing the internal expansions of springs representing the steel‐concrete interface within the RBSM. The applicability of the system is verified using both synthetic crack width data and crack data collected from in‐house laboratory testing. In the laboratory testing, corrosion levels were quantified by 3D scanning of the extracted reinforcing bars. The simulation results agree with the corrosion measurements, demonstrating the potential of the MPC‐RBSM system for predicting the corrosion distribution along reinforcing bars using surface crack data.