<abstract xmlns="http://www.w3.org/1999/xhtml"><p>The article presents a method of calibration of material parameters of a numerical model based on a genetic algorithm, which allows to match the calculation results with measurements from the geotechnical monitoring network. This method can be used for the maintenance of objects managed by the observation method, which requires continuous monitoring and design alterations. The correctness of the calibration method has been verified on the basis of artificially generated data in order to eliminate inaccuracies related to approximations resulting from the numerical model generation. Using the example of the tailing dam model the quality of prediction of the selected measurement points was verified. Moreover, changes of factor of safety values, which is an important indicator for designing this type of construction, were analyzed. It was decided to exploit the case of dam of reservoir, which is under continuous construction, that is dam height is increasing constantly, because in this situation the use of the observation method is relevant.</p></abstract>

The article presents a method of calibration of material parameters of a numerical model based on a genetic algorithm, which allows to match the calculation results with measurements from the geotechnical monitoring network. This method can be used for the maintenance of objects managed by the observation method, which requires continuous monitoring and design alterations. The correctness of the calibration method has been verified on the basis of artificially generated data in order to eliminate inaccuracies related to approximations resulting from the numerical model generation. Using the example of the tailing dam model the quality of prediction of the selected measurement points was verified. Moreover, changes of factor of safety values, which is an important indicator for designing this type of construction, were analyzed. It was decided to exploit the case of dam of reservoir, which is under continuous construction, that is dam height is increasing constantly, because in this situation the use of the observation method is relevant.

Numerical analysis of tailing dam with calibration based on genetic algorithm and geotechnical monitoring data

Wroclaw University of Science and Technology

Studia Geotechnica et Mechanica

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

The article presents a method of calibration of material parameters of a numerical model based on a genetic algorithm, which allows to match the calculation...

Numerical analysis of tailing dam with calibration based on genetic algorithm and geotechnical monitoring data

Article Category: Original Study

Online veröffentlicht: 24. Nov. 2020

Seitenbereich: 34 - 47

Eingereicht: 23. Juli 2020

Akzeptiert: 21. Sept. 2020

DOI: https://doi.org/10.2478/sgem-2020-0008

Schlüsselwörter
soil parameters, optimization, slope stability, genetic algorithm, observational method, monitoring

© 2021 Szczepan Grosel, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Numerical analysis of tailing dam with calibration based on genetic algorithm and geotechnical monitoring data

Article Category: Original Study

Online veröffentlicht: 24. Nov. 2020

Seitenbereich: 34 - 47

Eingereicht: 23. Juli 2020

Akzeptiert: 21. Sept. 2020

DOI: https://doi.org/10.2478/sgem-2020-0008

Schlüsselwörtersoil parameters, optimization, slope stability, genetic algorithm, observational method, monitoring

© 2021 Szczepan Grosel, published by Sciendo

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.

Schlüsselwörter
soil parameters, optimization, slope stability, genetic algorithm, observational method, monitoring