A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Monitoring and Modelling of Embankment Dams
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 ...
Monitoring and Modelling of Embankment Dams
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 ...
Monitoring and Modelling of Embankment Dams
Toromanovic, Jasmina (author)
2024-01-01
Doctoral thesis / Luleå University of Technology 1 jan 1997 → …, 1402-1544
Theses
Electronic Resource
English
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