A novel approach and program are developed for deterioration and predictive modeling of concrete bridge decks based on nondestructive evaluation (NDE) data. Through an iterative process - combined with data processing, bridge deck segmentation, regression analysis, data integration, and deterioration and predictive modeling - the developed program aids estimates of the remaining service life of bridge decks. Data collected on an actual bridge deck during a period of five and half years are used to illustrate the operation and performance of the developed program. Based on evaluation of condition maps, condition indices, and deterioration curves developed for a range of input parameters, the proposed method quantifies progression of deterioration in bridge deck. By reviewing the predictive models, combined with segmentation of the bridge deck area, a more realistic and practical estimation of the deck's remaining service life can be made. It is anticipated that the proposed method will provide objective and comprehensive evaluation and prediction of bridge deck condition based on data from multiple NDE technologies.
The authors sincerely acknowledge FHWA support for the Long-Term Bridge Performance (LTBP) Program provided by. The authors are also grateful to the Virginia Department of Transportation for providing access to the bridges in this study. The authors thank the research staff and students at Rutgers\u2019 Center for Advanced Infrastructure and Transportation for their help in data collection. This work was also supported by a National Research Foundation of Korea (NRF) grant (No. NRF-2018R1C1B5031504) and the new faculty research fund of Ajou University.
