Investigation of mechanistic deterioration modeling for bridge design and management
Date
2017
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Abstract
The ongoing deterioration of highway bridges in Colorado dictates that an effective method for allocating limited management resources be developed. In order to predict bridge deterioration in advance, mechanistic models which analyze the physical processes causing deterioration are capable of supplementing purely statistical models and addressing limitations associated with bridge inspection data and statistical methods. A review of existing analytical models in the literature was conducted. Due to its prevalence throughout the state of Colorado and frequent need for repair, corrosion-induced cracking of reinforced concrete (RC) decks was selected as the mode of deterioration for further study. A mechanistic model was developed to predict corrosion and concrete cracking as a function of material and environmental inputs. The model was modified to include the effects of epoxy-coated rebar, waterproofing membranes, asphalt overlays, joint deterioration, and deck maintenance. Probabilistic inputs were applied to simulate inherent randomness associated with deterioration. Model results showed that mechanistic models may be able to address limitations of statistical models and provide a more accurate and precise prediction of bridge degradation in advance. Preventative maintenance may provide longer bridge deck service life with fewer total maintenance actions than current methods. However, experimental study of specific deterioration processes and additional data collection are needed to validate model predictions. Maintenance histories of existing bridges are necessary to predicting bridge deterioration and improving bridge design and management in the future.
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Subject
mechanistic deterioration
bridge management