Parameter identification for an embankment dam using noisy field data

Field sampling for evaluation of mechanical behaviour in embankment dams is not easily performed, because the performance and the safety of the structure may be unfavourably affected. A non-destructive method, inverse analysis, is an alternative. In this study, inverse analysis has been utilised to identify values of soil parameters for an embankment dam. An objective function and a genetic search algorithm were combined with finite-element software to perform the analysis. Values of model parameters were calibrated until inclinometer deformations from monitoring and computations corresponded to each other. Errors in field measurements occur, related to – for example – measurement precision, as well as handling and installation of the equipment. Search algorithms in mathematical optimisation might incur numerical problems if they are used against data containing errors. The performance of the genetic algorithm was investigated for the dam studied, when identification was performed against inclinometer data containing known errors of different magnitudes. The results showed that the genetic algorithm can search for solutions without obtaining numerical problems, even though the field data are substantially perturbed. It was found that the genetic algorithm is able to find good solutions for data from field measurements, including the usual errors in practical dam applications.