Tolerance-based Pareto optimality for structural identification accounting for uncertainty

Structural parameter identifcation often requires an estimate, at least in a qualitative fashion, of the uncertainty of the solution. This uncertainty quantifcation should account for the sensitivity of the response to the sought parameters, the error in the measurement and the repeatability of the test. In this paper, repeatability is taken into account into a multi-objective framework, while a non-standard defnition of Pareto dominance based on a given tolerance in the objective satisfaction allows one to consider uncertainty in the experimental data. The solution of the identifcation is not given as a single value, but a region of the parameter space which is compatible with the data and accounts for uncertainties and response sensitivity to model parameters. The procedure is applied to an experimental test on a masonry panel, showing its e?ectiveness in discriminating identifable parameters from those a?ected by higher uncertainty.