Multi-objective whole-process inverse analysis method for excavation deformation of high slope
Slope engineering assesses excavation risks by predicting post-excavation displacement changes,and the value of rock mass engineering parameters is directly related to the final results.To obtain accurate and reasonable rock mass engineering parameters,a multi-objective inverse analysis method of slope deformation is adopted.This method is based on non-inferior sorting genetic algorithm Ⅲ(NSGA-Ⅲ),employs trained back propagation neural network(BPNN)to replace numerical calculations,and utilize NSGA-Ⅲ to search for the Pareto solution sets of multi-objective equations.The proposed method is validated against the dam abutment slope on the left bank of the first stage of the Jinping Hydropower Station.Considering four types of on-site data,namely horizontal and vertical displacements of external monitoring points,shallow slope surface displacements,and deep crack deformations,five kinds of rock mass material parameters with significant sensitivity to displacement changes are selected as inversion parameters,and parameter inversion is conducted under different combinations of objective functions.The results indicate that the inverse analysis method of NSGA-Ⅲ can comprehensively utilize a variety of monitoring data,and improve the reliability and computational efficiency of the inversion results.After forward calculation using the obtained material parameters from the inversion,the deformation obtained matches well with actual observation results,which verifies the accuracy and reliability of the proposed deformation prediction method in slope excavation engineering.
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