ABSTRACT
The effective management of bridge maintenance activities requires planning for necessary interventions in the future. Such planning is crucial to establish maintenance schedules with minimal life cycle costs and environmental impacts. Achieving this depends on reliable deterioration prediction models that consider key factors influencing deterioration and the associated uncertainties. Presently, predominant deterioration models in practice use inspection data and Markov models with the assumption of constant deterioration rates. However, factors like age, maintenance activities, traffic variations, and climate change can alter deterioration rates and transition probabilities of bridge elements over time. Climate change, particularly, with rising temperatures and extreme weather events, accelerates bridge deterioration. This study provides an overview of deterioration prediction models capable of accounting for temporal dynamics of bridge deterioration, where time-variant transition probabilities are modelled as functions of the factors influencing the deterioration process. Subsequently, it discusses their merits and challenges for practical implementation.
