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• W2904559133 abstract "The successful prediction of civil infrastructure’s deterioration process is crucial for making optimal maintenance, rehabilitation, and replacement (MR&R) decisions under financial constraints. The majority of current deterioration models simulate the deterioration process of a single structure element of civil infrastructure; such models thus ignore the interaction between dependent elements. However, the interaction between structure elements often plays an important role in the deterioration of the overall structure. Therefore, the primary objective of this paper is to address the interaction of these structure elements by developing a method to simulate the deterioration process of civil infrastructure on a system level. The proposed method will also provide a measure of the uncertainty of the simulation using Markov chain Monte Carlo (MCMC) to estimate the optimal parameters of the Markov chain and the probability distribution of those parameters. The Monte Carlo simulation is then used to generate a large number of deterioration process samples, which serve as the base of the uncertainty analysis of the simulation. The model was applied to simulate the deterioration process of a bridge element subsystem as an example application. In this example application, the model was calibrated and evaluated by the bridge inspection record collected in the Commonwealth of Virginia. The results demonstrate that including the interaction between elements in the model improves the accuracy of deterioration simulation while also reducing the uncertainty of the results. Furthermore, the proposed model is relatively easy to implement in current infrastructure management systems (IMSs) compared with other methods such as neural networks and fuzzy logical models." @default.
• W2904559133 created "2018-12-22" @default.
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• W2904559133 date "2019-03-01" @default.
• W2904559133 modified "2023-09-27" @default.
• W2904559133 title "Condition State–Based Civil Infrastructure Deterioration Model on a Structure System Level" @default.
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• W2904559133 doi "https://doi.org/10.1061/(asce)is.1943-555x.0000459" @default.
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