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Study on deformation mechanism and parameter inversion of a reservoir bank slope during initial impoundment
https://orcid.org/http://orcid.org/0000-0001-6703-6604
The stability of reservoir bank slope during impoundment is significant for the safe operation of hydropower stations. The deformation evolution of a slope adjacent to dam is analyzed based on the field monitoring data. The main influencing factors and spatial distribution of the slope deformation during impoundment are identified based on the multiple regression model and K-means cluster analysis, respectively. Subsequently, the deformation mechanism of the slope is analyzed by three-dimensional nonlinear finite element method. Then, an inversion analysis method based on improved adaptive genetic algorithm and back propagation neural network is proposed. The measured deformations of 44 monitoring points are used to inverse a total of 27 mechanical parameters, including deformation parameters, strength parameters and Biot coefficients of 9 materials. Finally, the influence of sample numbers on the prediction accuracy and the robustness of the neural network are discussed. The results indicate that the deformation rate of the slope is substantially associated with the impounding process. The water pressure component and aging component of the deformation account for a relatively high proportion while the temperature component is negligible. The deformation is mainly affected by material softening and effective stress of shallow-buried fractured rock mass, in which the latter dominates. The water load on the dam surface is the deformation inducement of the deep rock mass. The proposed inversion method can reasonably obtain the weakening rate of materials and make the numerical model accurately fit in with the actual state of the slope.
Study on deformation mechanism and parameter inversion of a reservoir bank slope during initial impoundment
https://orcid.org/http://orcid.org/0000-0001-6703-6604
The stability of reservoir bank slope during impoundment is significant for the safe operation of hydropower stations. The deformation evolution of a slope adjacent to dam is analyzed based on the field monitoring data. The main influencing factors and spatial distribution of the slope deformation during impoundment are identified based on the multiple regression model and K-means cluster analysis, respectively. Subsequently, the deformation mechanism of the slope is analyzed by three-dimensional nonlinear finite element method. Then, an inversion analysis method based on improved adaptive genetic algorithm and back propagation neural network is proposed. The measured deformations of 44 monitoring points are used to inverse a total of 27 mechanical parameters, including deformation parameters, strength parameters and Biot coefficients of 9 materials. Finally, the influence of sample numbers on the prediction accuracy and the robustness of the neural network are discussed. The results indicate that the deformation rate of the slope is substantially associated with the impounding process. The water pressure component and aging component of the deformation account for a relatively high proportion while the temperature component is negligible. The deformation is mainly affected by material softening and effective stress of shallow-buried fractured rock mass, in which the latter dominates. The water load on the dam surface is the deformation inducement of the deep rock mass. The proposed inversion method can reasonably obtain the weakening rate of materials and make the numerical model accurately fit in with the actual state of the slope.
Study on deformation mechanism and parameter inversion of a reservoir bank slope during initial impoundment
https://orcid.org/http://orcid.org/0000-0001-6703-6604
The stability of reservoir bank slope during impoundment is significant for the safe operation of hydropower stations. The deformation evolution of a slope adjacent to dam is analyzed based on the field monitoring data. The main influencing factors and spatial distribution of the slope deformation during impoundment are identified based on the multiple regression model and K-means cluster analysis, respectively. Subsequently, the deformation mechanism of the slope is analyzed by three-dimensional nonlinear finite element method. Then, an inversion analysis method based on improved adaptive genetic algorithm and back propagation neural network is proposed. The measured deformations of 44 monitoring points are used to inverse a total of 27 mechanical parameters, including deformation parameters, strength parameters and Biot coefficients of 9 materials. Finally, the influence of sample numbers on the prediction accuracy and the robustness of the neural network are discussed. The results indicate that the deformation rate of the slope is substantially associated with the impounding process. The water pressure component and aging component of the deformation account for a relatively high proportion while the temperature component is negligible. The deformation is mainly affected by material softening and effective stress of shallow-buried fractured rock mass, in which the latter dominates. The water load on the dam surface is the deformation inducement of the deep rock mass. The proposed inversion method can reasonably obtain the weakening rate of materials and make the numerical model accurately fit in with the actual state of the slope.
Study on deformation mechanism and parameter inversion of a reservoir bank slope during initial impoundment
Acta Geotech.
Zhuang, Wenyu (author) / Liu, Yaoru (author) / Zhang, Rujiu (author) / Hou, Shaokang (author) / Yang, Qiang (author)
Acta Geotechnica ; 18 ; 4353-4374
2023-08-01
22 pages
Article (Journal)
Electronic Resource
English
Deformation mechanism , IAGA–BPNN , Multiple regression , Parameter inversion , Reservoir bank slope , Water–rock interaction Engineering , Geoengineering, Foundations, Hydraulics , Solid Mechanics , Geotechnical Engineering & Applied Earth Sciences , Soil Science & Conservation , Soft and Granular Matter, Complex Fluids and Microfluidics
Statistical modelling for high arch dam deformation during the initial impoundment period
| Wiley | 2020