Abstract
Various infrastructure information is gathered nowadays in databases, which have become rather large after years of development and data collection. For thorough search and broad exploitation of the available information, even beyond its original scope, advanced data analysis approaches need to be employed. The present work is concerned with the exploitation of the data in the US National Bridge Inventory (NBI) maintained by the Federal Highway Administration (FHWA), which includes information for over 500,000 bridges. The information provided in NBI was analyzed in combination with additional data from other sources (for climatic conditions, earthquake hazard, etc.). Where needed, data were converted to correspond to bridge locations using spatial interpolation techniques. Then, Exploratory Data Analysis (EDA), Analysis of Variance (ANOVA) and regression analysis methods were utilized to study the causes of bridge deterioration. These statistical methods yield quantitative results and allow the identification, ranking and measurement of intensity of factors contributing to the decrease of the structural condition of bridges with time.
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Alogdianakis, F., Charmpis, D.C., Balafas, I. (2021). Using Data Analysis to Extract Structural Deterioration Information from the US National Bridge Inventory Database. In: Pereira, E.B., Barros, J.A.O., Figueiredo, F.P. (eds) Proceedings of the 3rd RILEM Spring Convention and Conference (RSCC2020). RSCC 2020. RILEM Bookseries, vol 32. Springer, Cham. https://doi.org/10.1007/978-3-030-76547-7_22
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DOI: https://doi.org/10.1007/978-3-030-76547-7_22
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