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자료유형
학술저널
저자정보
Zambon, Ivan (Department of Civil Engineering and Natural Hazards, University of Natural Resources and Life Sciences) Vidovic, Anja (Department of Civil Engineering and Natural Hazards, University of Natural Resources and Life Sciences) Strauss, Alfred (Department of Civil Engineering and Natural Hazards, University of Natural Resources and Life Sciences) Matos, Jose (Civil Engineering Department, Campus de Azurem, Minho University) Friedl, Norbert (Bridge Construction and Structural Engineering, O BB-Infrastruktur AG)
저널정보
테크노프레스 Smart structures and systems Smart structures and systems 제21권 제3호
발행연도
2018.1
수록면
305 - 320 (16page)

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The second half of the 20th century was marked with a significant raise in amount of railway bridges in Austria made of reinforced concrete. Today, many of these bridges are slowly approaching the end of their envisaged service life. Current methodology of assessment and evaluation of structural condition is based on visual inspections, which, due to its subjectivity, can lead to delayed interventions, irreparable damages and additional costs. Thus, to support engineers in the process of structural evaluation and prediction of the remaining service life, the Austrian Federal Railways (${\ddot{O}}$ BB) commissioned the formation of a concept for an anticipatory life cycle management of engineering structures. The part concerning concrete bridges consisted of forming a bridge management system (BMS) in a form of a web-based analysis tool, known as the LeCIE_tool. Contrary to most BMSs, where prediction of a condition is based on Markovian models, in the LeCIE_tool, the time-dependent deterioration mechanisms of chloride- and carbonation-induced corrosion are used as the most common deterioration processes in transportation infrastructure. Hence, the main aim of this article is to describe the background of the introduced tool, with a discussion on exposure classes and crucial parameters of chloride ingress and carbonation models. Moreover, the article presents a verification of the generated analysis tool through service life prediction on a dozen of bridges of the Austrian railway network, as well as a case study with a more detailed description and implementation of the concept applied.

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