Life Cycle Assessment Framework for the U.S. Bridge Inventory. Issue 12 (December 2018)

• Record Type: Journal Article
• Authors: Babanajad, Saeed; Bai, Yun; Wenzel, Helmut; Wenzel, Moritz; Parvardeh, Hooman; Rezvani, Ali; Zobel, Robert; Moon, Franklin; Maher, Ali
• Is Part Of: Transportation research record. Volume 2672:Issue 12(2018)
• Page Start: 82
• Page End: 92
• Publication Date: 2018-12
• Subjects: Transportation -- Periodicals; Roads; Transport -- Périodiques; Routes -- Périodiques; Routes -- Conception et construction -- Périodiques; Roads; Transportation; 388.05
• DOI: 10.1177/0361198118781396
• Languages: English
• ISSNs: 0361-1981

Abstract

The effective management of bridges requires a good understanding of their life expectancies. Improved prediction of bridge service life is required to be developed in order to better understand bridge deterioration and to find more effective maintenance and repair strategies. These models are integral components of the Long-Term Bridge Performance Program (LTBP), a 20-year research effort initiated by the U.S. Federal Highway Administration (FHWA) to improve the understanding of bridge performance. In this paper, the development of a life expectancy model framework, as part of the research effort in this program, is presented. The framework is established based on a semi-probabilistic approach to adherently maintain the advantages of both deterministic and probabilistic techniques. The modeling follows a step-by-step process which incorporates data collected from historical records, training the data, creating a model based on the most suitable approach, and reducing the associated uncertainties. The basic model is first trained by the network of bridge inventory and the uncertainties are reflected by determining lower and upper margins. Then the model is improved by introducing the new knowledge gained from the external attributes influencing the structure. Finally, the condition states of the bridge components are employed directly to refine the model for realistic assessment. The developed model is later automated into the Bridge Portal, the main core of the bridge-performance data warehouse. A detailed example using the Mid-Atlantic cluster bridge inventory data is presented in this paper to illustrate the application of the method described above.