In this paper, Artificial Neural Networks (ANN) have been utilized to predict the stability of a planar tunnel heading in rock mass based on the well-defined Hoek–Brown (HB) yield criterion. The HB model was developed to capture the failure criterion of rock masses. To provide the datasets for an ANN model, the numerical upper bound (UB) and lower bound (LB) solutions obtained from the finite element limit analysis (FELA) with the HB failure criterion for the problem of tunnel headings are derived. The sensitivity analysis of all influencing parameters on the stability of rock tunnel heading is then performed on the developed ANN model. The proposed solutions will enhance the dependability and preciseness of predicting the stability of rock tunnel heading. Note that the effect of the unlined length ratio has not been explored previously but has been found to be of critical importance and significantly contributes to the failure of rock tunnel heading. By utilizing the machine learning-aided prediction capability of the ANN approach, the numerical solutions of the stability of tunnel heading can be accurately predicted, which is better than the use of the classic linear regression approach. Thus, providing a better and much safer assessment of mining or relatively long-wall tunnels in rock masses.
This work is licensed under a Creative Commons Attribution-NonCommercial 3.0 Unported License Newcastle University ePrints-eprint.ncl.ac.uk Cabangon LT, Elia G, Rouainia M. Modelling the transverse behaviour of circular tunnels in structured clayey soils during earthquakes.
The stability of unsupported rectangular excavations in undrained clay is examined under the influence of anisotropy and heterogeneity using the three-dimensional finite element upper and lower bound limit analysis with the Anisotropic Undrained Shear (AUS) failure criterion. Three anisotropic undrained shear strengths are considered in the study, namely triaxial compression, triaxial extension, and direct simple shear. Special considerations are given to the study of the linearly-increased anisotropic shear strengths with depth. The numerical solutions are presented by an undrained stability number that is a function of four dimensionless parameters, i.e., the excavated depth ratio, the aspect ratio of the excavated site, the shear strength gradient ratio, and the anisotropic strength ratio. To the authors’ best knowledge, this is the first of its kind to present the stability solutions of 3D excavation considering soil anisotropy and heterogeneity. As such, this paper introduces a novel approach for predicting the stability of unsupported rectangular excavation in undrained clays in 3D space, accounting for soil anisotropy and non-homogeneity. Notably, it develops a basis to formulate a mathematical equation and design charts for estimating the stability factor of such type of excavation, which should be of great interest to engineering practitioners.
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