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Probabilistic Data-driven Assessment of Pavement Management Systems



Data driven pavement management is the key to accurate budget allocation and treatment selection of deteriorating pavements. Network monitoring frequency and applied treatment strategies can make drastic changes in final overall life cycle cost of sections, and therefore associated risks need to be considered. In this study, first the current state of practice and application of pavement management systems in city of Norwalk, Connecticut is analyzed. Then, life cycle cost analysis (LCCA) is performed on the available data. Results of these analyses are used to study two scopes: financial consequences of maintenances activities, and financial consequences of inspection cycles. Finally, a probabilistic approach offers risk factors and financial consequences of different treatment strategies and inspection cycles over the analysis period.

doi: 10.12783/SHM2015/298

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