[HTML][HTML] Challenges associated with numerical back analysis in rock mechanics

G Walton, S Sinha - Journal of Rock Mechanics and Geotechnical …, 2022 - Elsevier
Numerical back analysis is a valuable tool available to rock mechanics researchers and
practitioners. Recent studies related to back analysis methods focused primarily on …

Back analysis of rock mass parameters in tunnel engineering using machine learning techniques

X Chang, H Wang, Y Zhang - Computers and Geotechnics, 2023 - Elsevier
Efficient determination of the rock mass properties is vitally important for calculating and
evaluating tunnel stability in tunnel engineering. The back analysis method has been widely …

Composite interpretability optimization ensemble learning inversion surrounding rock mechanical parameters and support optimization in soft rock tunnels

J Cui, S Wu, H Cheng, G Kui, H Zhang, M Hu… - Computers and …, 2024 - Elsevier
The mechanical parameters of the surrounding rock of a tunnel are the premise and
foundation of the supporting design in soft rock tunnel engineering. To obtain the …

Inversion of Surrounding Rock Mechanical Parameters in a Soft Rock Tunnel Based on a Hybrid Model EO-LightGBM

J Sun, S Wu, H Wang, T Wang, X Geng… - Rock Mechanics and Rock …, 2023 - Springer
The mechanical parameters of the surrounding rock are the critical factors considered in the
design and construction of tunnels, especially soft rock tunnels. The accuracy of obtained …

Inverse modeling of seepage parameters based on an improved gray wolf optimizer

Y Shu, Z Shen, L Xu, J Duan, L Ju, Q Liu - Applied Sciences, 2022 - mdpi.com
The seepage parameters of the dam body and dam foundation are difficult to determine
accurately and quickly. Based on the inverse analysis, a Gray Wolf Optimizer (GWO) was …

Study on deformation mechanism and parameter inversion of a reservoir bank slope during initial impoundment

W Zhuang, Y Liu, R Zhang, S Hou, Q Yang - Acta Geotechnica, 2023 - Springer
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 …

Machine-learning method applied to provide the best predictive model for rock mass deformability modulus (Em)

EE Meybodi, A DastBaravarde… - Environmental …, 2023 - search.proquest.com
Rock mass classification systems are used to estimate deformability modulus. This study
offers a relationship to estimate deformability modulus using geomechanical rock …

Application of the ridge regression in the back analysis of a virgin stress field

W Meng, C He, Z Zhou, Y Li, Z Chen, F Wu… - Bulletin of Engineering …, 2021 - Springer
When the least square approach is used to solve regression coefficients during the back
analysis of a virgin stress field, the multicollinearity among independent variables may …

Machine-learning method applied to provide the best predictive model for rock mass deformability modulus (Em)

E Emami Meybodi, A DastBaravarde… - Environmental Earth …, 2023 - Springer
Rock mass classification systems are used to estimate deformability modulus. This study
offers a relationship to estimate deformability modulus using geomechanical rock …

[HTML][HTML] In situ stress inversion using nonlinear stress boundaries achieved by the bubbling method

X Liu, C Huang, W Zhu, J Oh, C Zhang, G Si - Journal of Rock Mechanics …, 2024 - Elsevier
Due to the heterogeneity of rock masses and the variability of in situ stress, the traditional
linear inversion method is insufficiently accurate to achieve high accuracy of the in situ …