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Increasing requirements on the infrastructure caused by more and heavier traffic coincide with both the aging and the progressive degradation of bridge constructions. These exemplary issues lead to a non-negligible need for reassessments of existing bridges. Compared to the new building design, safety reserves can be used in the evaluation of such existing structures, since uncertainties that may arise during the design, construction and previous Service time are better known or no longer present. Uncertainties can be evaiuated more precisely by measurements. In the meantime, the application of advanced NDT-methods on concrete structures have become so capable, that crucial structure Parameters like certain material properties or geometrical dimensions can be quantified without significant destructive interventions. The measured data can be explicitly incorporated into the probabilistic computation models used for the bridge reassessment in form of random variables. Therewith, a previously insufficient model can be refined to achieve a higher level of approximation. This contribution emphasises two fundamental steps of the measured data based probabilistic reassessment: The sensitivity analyses to identify the cruciai Parameters and the needed accuracy of the related information as well as the comparison with expected uncertainties of non-destructively measured Parameters.
The reassessment of bridges is becoming increasingly important. The basic requirement for analyses of structural safety is reliable knowledge about individual structures. This paper introduces the new approach to evaluate the quality of measured data gained from non-destructive testing (NDT) to provide reliable, objective, and relevant information about existing bridges. The purpose is to relate this validated knowledge to probabilistic analyses. Bridging the gap between NDT and numerical reassessments indicates reduced numerical uncertainties and residual service time extensions. This paper deals with an application of this approach using measurement data collected by ultrasonic technique at a prestressed concrete bridge.