PROBABILISTIC DESIGN FRAMEWORK FOR SUSTAINABLE REPAIR AND REHABILITATION OF CIVIL INFRASTRUCTURE

This paper presents a probabilistic-based framework for the design of civil infrastructure repair and rehabilitation to achieve targeted improvements in sustainability indicators. The framework consists of two types of models: (i) service life prediction models combining one or several deterioration mechanisms with a suite of limit states and (ii) life cycle assessment (LCA) models for measuring the impact of a given repair, rehabilitation, or strengthening. The first type of model estimates the time to the first repair (from the time of initial construction) and given the structural condition after a repair the time to any subsequent repair. The second type of model estimates the impact of the chosen repair or rehabilitation based on a process-based LCA of individual repair activities. Both models (service life or LCA) are formulated stochastically so that the time to repair and total impact are described by a probability density function. This leads to a fully probabilistic calculation of accrued cumulative impacts (which can be annualized) throughout the service life of a structure from initial construction up to the time of functional obsolescence (end of life). These are then compared to design targets taken from policy goals such as the Intergovernmental Panel on Climate Change's 4th Assessment Report (IPCC AR4).