Polynomial Chaos Representation for Identification of Mechanical Characteristics of Instrumented Structures

The modeling of in-service behavior is of first importance when reassessing complex structures like harbor structures and when performing risk analysis. To this aim, the monitoring of structures allows assessment of the level of loading and to provide more realistic models for mechanical behavior or input values for their parameters. Moreover, for complex structures and due to building hazards, a stochastic modeling is needed to represent the large scatter of measured quantities. In this article, a step-by-step procedure for structural identification is presented. A decomposition of random variables on Polynomial Chaos is selected and it is shown to represent better the basic variables in comparison to preselected distribution functions, when considering maximum likelihood estimate. The decomposed variables are used for a stochastic analysis to be further updated with available monitoring data. The model can be used to follow the structure behavior during in-service or extreme conditions and to perform a reliability analysis. The proposed procedure will be carried out by using available data from the monitoring of a pile-supported wharf in the Port of Nantes, in France, but it can be generalized to similar monitored structures.