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Effects of Measurement Error on the Genetic Algorithm in Soil Parameter Identification for an Earth- and Rockfill Dam
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.ORCID iD: 0000-0001-6562-1738
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.ORCID iD: 0000-0003-3031-816X
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.ORCID iD: 0000-0003-1935-1743
2017 (English)In: ICSMGE 2017: 19th International Conference on Soil Mechanics and Geotechnical Engineering, 19th ICSMGE Secretariat , 2017, p. 2443-2446Conference paper, Published paper (Refereed)
Abstract [en]

It is usually difficult to determine values for soil parameter values in earth- A nd rockfill dams by traditional methods. Field sampling is not easily performed, especially in the impervious parts, since the performance and safety of the dam structure may be affected in an unfavourable way. Therefore other methods, preferably non-destructive, are needed to investigate the mechanical behaviour. Inverse analysis has been utilised to identify soil parameter values for an earth- A nd rockfill dam. An error function and a genetic search algorithm were combined with a finite element software to perform the analysis. The model parameters in the chosen constitutive model were calibrated until the horizontal deformations corresponded to the horizontal inclinometer deformations. Errors or irregularities in field measurements can occur, for instance based on the accuracy of the equipment. In this study, the performance of the genetic algorithm was investigated, when applied to identify soil parameters for a dam. Added perturbations to simulated inclinometer data are randomly generated within a chosen interval of error. The results showed that the genetic algorithm found a minimum for the error function even though the field data was substantially perturbed. Errors up to 10% were shown to have minor impact

Place, publisher, year, edition, pages
19th ICSMGE Secretariat , 2017. p. 2443-2446
National Category
Geotechnical Engineering
Research subject
Soil Mechanics
Identifiers
URN: urn:nbn:se:ltu:diva-64847Scopus ID: 2-s2.0-85045198380OAI: oai:DiVA.org:ltu-64847DiVA, id: diva2:1121328
Conference
19th International Conference on Soil Mechanics and Geotechnical Engineering, ICSMGE 2017, Seoul, South Korea, 17-22 September 2017
Available from: 2017-07-10 Created: 2017-07-10 Last updated: 2020-04-20Bibliographically approved

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Scopushttps://www.issmge.org/uploads/publications/1/45/06-technical-committee-16-tc210-21.pdf

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Toromanovic, JasminaMattsson, HansLaue, Jan

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