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Parameter identification for an embankment dam using noisy field data
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: 0000-0002-1365-8552
Luleå University of Technology, Department of Civil, Environmental and Natural Resources Engineering, Mining and Geotechnical Engineering.ORCID iD: 0000-0003-1935-1743
2020 (English)In: Proceedings of the Institution of Civil Engeneers: Geotechnical Engineering, ISSN 1353-2618, E-ISSN 1751-8563, Vol. 173, no 6, p. 519-534Article in journal (Refereed) Published
Abstract [en]

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.

Place, publisher, year, edition, pages
Institution of Civil Engineers (ICE) , 2020. Vol. 173, no 6, p. 519-534
Keywords [en]
computational mechanics, earth dams, noise
National Category
Geotechnical Engineering
Research subject
Soil Mechanics
Identifiers
URN: urn:nbn:se:ltu:diva-77527DOI: 10.1680/jgeen.19.00163ISI: 000589868200005Scopus ID: 2-s2.0-85095975020OAI: oai:DiVA.org:ltu-77527DiVA, id: diva2:1388710
Note

Validerad;2020;Nivå 2;2020-11-23 (alebob)

Available from: 2020-01-27 Created: 2020-01-27 Last updated: 2024-04-26Bibliographically approved
In thesis
1. Monitoring and Modelling of Embankment Dams
Open this publication in new window or tab >>Monitoring and Modelling of Embankment Dams
2024 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Modelling can be used as a tool for prediction of the behaviour of embankment dams as a part of the dam safety work. It is advantageous to predict the performance and compare to measurements done, to obtain more knowledge about the dam behaviour, as these structures are complex and potential failures are hazardous. The research presented in this thesis covers parameter identification by backanalysis, interpretation of dam measurements and numerical predictions of dam behaviour. The research highlights the role of numerical modelling as a supportive tool in dam engineering, ratherthan a standalone technique. Two embankment dams were analysed in the research: a 45 metres high existing hydropower dam and a four metres high experimental dam built during the project.

The soil materials in an embankment dam vary significantly, as the zones in a dam have different functions. To create reliable numerical models, parameter values defining the stress-strain relationship of the materials are needed. Obtaining such information for existing embankment dams poses challenges, often due to limited available data and the potential risks associated with traditional field sampling methods. In previous research at Luleå University of Technology, inverse analysis was successfully applied to embankment dam calibration of finite element models against field measurements, by utilizing an optimisation code with a genetic algorithm for optimisation. Inverse analysis provides a non-destructive method for obtaining information about the stress-strain relationship of the material in a dam.

First, applications of inverse analysis are exemplified on an existing embankment dam. The study investigates the impact on the inverse analysis methodology when errors occur in the field measurements. The employed genetic algorithm showed its robustness when dealing with errors, this is important since errors are likely to occur in field measurements. Thereafter, the study examined the usage of parameters identified through inverse analysis in predictions of deformations when a stabilising berm was constructed on the downstream shoulder. The predicted deformations were compared to deformations from inclinometer measurements. The trend of the measured deformations was replicated in the numerical model, and the magnitudes were in the right order. The study shows that predicting future dam behaviour based on results from inverse analysis can be done reasonably well in this case.

Second, the mechanical behaviour of an experimental embankment dam is interpreted and modelled. Monitoring of pore pressure was done with transducers that were installed at different levels covering the whole core and parts of the filters. Measurements were performed continuously. The response of pore pressure in the core, during impoundment and operation, are focused on. A significant delay of the saturation front was observed, as the pore pressure in the bottom of the downstream part of the core was not building up as expected during impoundment and operation. Fully-coupled numerical analyses were performed, in order to better understand the conditions of the core in the experimental dam. The core was initially assumed to be homogeneous, but the numerical results showed poor agreement with the observed behaviour from field. By further analysing the measurements and modelling, the experimental dam was found to be non-homogeneous, even though it was built under very controlled conditions. Variations in the hydraulic conductivity in the dam core were therefore introduced in the numerical model. The hydraulic conductivity changed with height in the dam, was different in the vertical and horizontal direction and was also changing with time at specific places in the core. With these numerical adjustments better correlations against measurements were obtained, compared to the homogeneous case, indicating that homogeneous conditions are not suitable for the core. The study also showed that the values of parameters obtained from laboratory testing are not suitable for the whole core, as the conditions assumed in laboratory do not correspond to the prevailing field conditions.

Measurements of the strain development in the bottom of the embankment dam was done by fibre optics. The settlements in the dam body after construction are captured, mainly as areas of higher lateral strain at the toes of the dam. The 1% sloping foundation towards the downstream side is captured. The measurements show that more shear is activated at the downstream side. Impoundment causes the largest strains, it can be observed that the strains vary in the different dam zones the bottom of the dam body.

In summary, the research presented in this thesis has shown how numerical modelling can be used as support in dam engineering, when combined with monitoring data. Values of parameters that would have been difficult to retrieve otherwise are obtained by inverse analysis, making it possible to perform more reliable predictions. The modelling has also helped to explain unexpected behaviour from monitoring of pore pressure. When the experimental dam was built, it was expected that the core would be homogeneous. The monitoring of the dam and the numerical modelling revealed that the core was non-homogeneous. The experimental dam is small, and it was constructed under very controlled forms. Therefore, it is reasonable to assume that it would be difficult to construct a homogeneous core in a real, large embankment dams. This is an important finding in the thesis, which can influence both how dams should be numerically modelled as well as how dam safety assessments during first impoundment and the beginning of the operation phase should be done.

Place, publisher, year, edition, pages
Luleå: Luleå University of Technology, 2024
Series
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, ISSN 1402-1544
National Category
Geotechnical Engineering
Research subject
Soil Mechanics
Identifiers
urn:nbn:se:ltu:diva-104920 (URN)978-91-8048-517-3 (ISBN)978-91-8048-518-0 (ISBN)
Public defence
2024-05-28, E632, Luleå University of Technology, Luleå, 13:00 (English)
Opponent
Supervisors
Available from: 2024-04-02 Created: 2024-03-28 Last updated: 2024-05-07Bibliographically approved

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