Parameter identification for an embankment dam using noisy field data. Issue 6 (19th December 2019)

• Record Type: Journal Article
• Authors: Toromanovic, Jasmina; Mattsson, Hans; Knutsson, Sven; Laue, Jan
• Is Part Of: Proceedings of ICE. Volume 172:Issue 6(2019:Dec.)
• Page Start: 1
• Page End: 42
• Publication Date: 2019-12-19
• Subjects: Computational mechanics -- earth dams -- noise; Geotechnical engineering -- Periodicals; 624.151
• DOI: 10.1680/jgeen.19.00163
• Languages: English
• ISSNs: 1353-2618

Abstract

Abstract : Field sampling for evaluation of the mechanical behaviour in embankment dams is not easily performed, since the performance and the safety of the structure may be unfavourably affected. A non-destructive method as inverse analysis is an alternative. In this study, inverse analysis has been utilised to identify values for soil parameters for an embankment dam. An objective function and a genetic search algorithm were combined with a 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 e.g. measurement precision as well as handling and installation of the equipment. Search algorithms in mathematical optimisation might obtain numerical problems if they are used against data containing errors. The performance of the genetic algorithm was investigated for the studied dam, 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 is substantially perturbed. It was found that the genetic algorithm is able to find good solutions for data from field measurements including usual errors in practical dam applications.