Quantifying the effects of modeling simplifications for structural identification of bridges

Several long span prestressed segmental box girder bridges were built in the early 1980's and many of them are affected by long-term residual deformations. Although models have been proposed to describe their structural behavior, several uncertainties remain. This paper examines the effects of errors introduced by model simplifications on predicted values. These results are used to improve the estimation of parameter values using model-based data-interpretation strategies. The procedure is illustrated for the Grand-Mere bridge located in Canada. This bridge is affected by excessive long-term vertical displacements. Model simplifications such as the degree of complexity of a model are found to have an important influence on prediction errors. Representing these errors by zero-mean independent Gaussian noise does not adequately describe the relationships between errors observed in this case study. Estimated errors are used during the interpretation of ambient vibration acceleration data recorded on the structure. The interpretation approach employed is based on error-domain model falsification. The study provides ranges of parameter values that can subsequently be used to characterize more accurately aspects such as long-term creep and shrinkage behavior.

Uncontrolled Keywords

Structural identification, model simplification, uncertainties, error-domain model falsification, ambient vibration monitoring, bridge, Finite elements