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The acquisition and appropriate processing of relevant information about the considered system remains a major challenge in assessment of existing structures. Both the values and the validity of computed results such as failure probabilities essentially depend on the quantity and quality of the incorporated knowledge. One source of information are onsite measurements of structural or material characteristics to be modeled as basic variables in reliability assessment. The explicit use of (quantitative) measurement results in assessment requires the quantification of the quality of the measured information, i.e., the uncertainty associated with the information acquisition and processing. This uncertainty can be referred to as measurement uncertainty. Another crucial aspect is to ensure the comparability of the measurement results.This contribution attempts to outline the necessity and the advantages of measurement uncertainty calculations in modeling of measurement data-based random variables to be included in reliability assessment. It is shown, how measured data representing time-invariant characteristics, in this case non-destructively measured inner geometrical dimensions, can be transferred into measurement results that are both comparable and quality-evaluated. The calculations are based on the rules provided in the guide to the expression of uncertainty in measurement (GUM). The GUM-framework is internationally accepted in metrology and can serve as starting point for the appropriate processing of measured data to be used in assessment. In conclusion, the effects of incorporating the non-destructively measured data into reliability analysis are presented using a prestressed concrete bridge as case-study.
"The reassessment of bridges continues to take great importance both nationally and internationally. A major challenge is to find computation models reflecting the actual properties of the considered structures sufficiently accurate. Besides regular inspections, the conduction of advanced measurements is suitable to generate reliable information about a structure to be assessed. Prior to incorporating measurement results in reassessment, the relevance, the trueness, and the precision of the measured information needs to be stated. On the one hand, the use of information whose quality has not been assessed can lead to errors with serious consequences. On the other, the measurement of irrelevant information is inefficient. Although the use of measured data in assessment is currently mostly unregulated, their appreciation in reliability analyses is beneficial since the built environment can be assessed more realistically. Utilizing NDT in reassessment has the potential to extend remaining lifetimes of a structure, save resources, and improve infrastructural availabilities. The power of judgment regarding the decision on the reliability of an existing structure can be increased.
In this contribution, an approach is outlined to process non-destructively gathered measurement data in a comparableway in order to include themeasured information in probabilistic reliability assessments of existing structures. An essential part is the calculation of measurement uncertainties. The effect of incorporating evaluated NDT-results is demonstrated by means of a prestressed concrete bridge and GPR measurements conducted on this bridge as a case-study. The bridge is assessed regarding SLS Decompression using the NDT-results."