Search

AbstractSimilar to pile group, the process of designing an anchor group requires the determination of an efficiency factor that describes the overlapping effects of neighboring anchors. This research article introduces an efficiency factor denoted as ξ, which represents the ratio of the ultimate uplift pressure of a single anchor within a group to the ultimate uplift pressure of an isolated anchor. The primary approach employed involves advanced 3D finite element limit analysis with an adaptive meshing technique, which can be utilized to examine the uplift stability problem of 3D anchor groups. Numerical findings are compared with those obtained from previous research, incorporating both experimental and analytical results. This would ensure that our results are validated and provide valuable information into the performance of anchor groups. In addition to these findings, we introduce a MARS machine learning model, which has been trained using a dataset of 875 data points. This model is designed to establish an empirical equation that can be practically used for design purposes. To further enhance our understanding, we present the relative importance index (RII). This index allows us to identify which factors have the most significant impact on the behavior of anchor groups. In conclusion, the results presented in this article are of practical significance for the geotechnical engineering community. [ABSTRACT FROM AUTHOR]

The paper presents axisymmetric FEA solutions for the bearing capacity of conical footings embedded in anisotropic and inhomogeneous clays using NGI-ADP model. The bearing capacity factor of conical footings is defined to be a function of three dimensionless parameters: (i) the cone apex angle, (ii) the increasing strength gradient ratio, and (iii) the anisotropic shear strength ratio. A series of parametric studies is carried out to portray the influence of all input parameters on the bearing capacity factors. Based on the FEA results of 216 investigated cases, the artificial neural network (ANN) is adopted to capture the relationship between input parameters and output bearing capacity factors. The complex relationship between input parameters and output bearing capacity is studied through the use of design charts and failure patterns. A new accurate equation with a high value of R2 is proposed and the sensitivity of each input parameter on the output results is scored by adopting the results from the ANN model. This study has provided some practical insights into the performance of conical footings embedded in anisotropic and inhomogeneous clays. [ABSTRACT FROM AUTHOR]