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Quantifying Uncertainty in Bridge Condition Assessment Data

The effectiveness of decisions in bridge management systems is based on the quality of data obtained regarding various processes in the systems. Hence, data play a crucial role in bridge management. In general, data collected has some amount of associated uncertainty. In order to assess the impact of this uncertainty on decisions, the uncertainty in the data should be quantified. In other words, by determining the level of uncertainty, we are judging the quality of the data, which is important for making effective decisions in bridge management systems. This paper describes a procedure for measuring the level of uncertainty in bridge condition assessment data. First, a bridge deterioration model was applied to historical data to estimate the current condition of a bridge and compared to current data. Next, reliability theory was applied to estimate the structural reliability of the bridge, again based on both historical and present data. Finally, the reliability of the bridge was compared to the results obtained from the deterioration model, using a coefficient of correlation. Because the deterioration model used Markov chains, which are probabilistic, and the reliability results are also reported as probabilities, the results can be compared.