A review of techniques, advances and outstanding issues in numerical modelling for rock mechanics and rock engineering

Structures in Other Domains The methodology of structural analysis discussed in this article has been applied beyond the narrow realm of natural language syntax that we have discussed in this article. Within the study of language, similar methods of analysis have been pervasively applied to the study of sounds (phonology), words (morphology), and meanings (semantics), yielding a range of of abstract structural representations whose properties bear considerable explanatory burden. There are a wealth of cases in each of these domains analogous to those discussed here, though space prevents us from going in these (see Akmajian, Demers, Farmer and Harnish 1995 for a traditional overview, and Jackendo 1994 for one more focused on connections with cognitive science). Additionally, these representations have shed substantial light on the processes of language acquisition and language change. It has been found that variation in the types of sentences that are used, whether during the course of children's acquisition of their native languages or in the centuries-long periods of linguistic change, are best characterized not as super cial and haphazard alterations, but rather in terms of parametric modi cations to the fundamental underlying grammatical rules and constraints. Moving outside the domain of language, one application of these same methods has been in the study of music cognition. Just as the representations of linguistic theory arise out of an attempt to model speakers' intuitions about well-formedness and possible meanings of the sentences of their

Structural analysis

Gravitational search algorithm is one of the new optimization algorithms that is based on the law of gravity and mass interactions. In this algorithm, the searcher agents are a collection of masses, and their interactions are based on the Newtonian laws of gravity and motion. In this article, a binary version of the algorithm is introduced. To evaluate the performances of the proposed algorithm, several experiments are performed. The experimental results confirm the efficiency of the BGSA in solving various nonlinear benchmark functions.

BGSA: binary gravitational search algorithm

Two-dimensional slope stability analysis by limit equilibrium and strength reduction methods

Accurate assessment of undrained shear strength (USS) for soft sensitive clays is a great concern in geotechnical engineering practice. This study applies novel data-driven extreme gradient boosting (XGBoost) and random forest (RF) ensemble learning methods for capturing the relationships between the USS and various basic soil parameters. Based on the soil data sets from TC304 database, a general approach is developed to predict the USS of soft clays using the two machine learning methods above, where five feature variables including the preconsolidation stress (PS), vertical effective stress (VES), liquid limit (LL), plastic limit (PL) and natural water content (W) are adopted. To reduce the dependence on the rule of thumb and inefficient brute-force search, the Bayesian optimization method is applied to determine the appropriate model hyper-parameters of both XGBoost and RF. The developed models are comprehensively compared with three comparison machine learning methods and two transformation models with respect to predictive accuracy and robustness under 5-fold cross-validation (CV). It is shown that XGBoost-based and RF-based methods outperform these approaches. Besides, the XGBoost-based model provides feature importance ranks, which makes it a promising tool in the prediction of geotechnical parameters and enhances the interpretability of model.

Prediction of undrained shear strength using extreme gradient boosting and random forest based on Bayesian optimization

Location of critical failure surface and some further studies on slope stability analysis

Particle swarm optimization algorithm for the location of the critical non-circular failure surface in two-dimensional slope stability analysis

Performance studies on six heuristic global optimization methods in the location of critical slip surface

An improved harmony search algorithm is proposed which is found to be more efficient than the original harmony search algorithm for slope stability analysis. The effectiveness of the proposed algorithm is examined by considering several published cases. The improved harmony search method is applied to slope stability problems with five types of procedure for generating trial slip surfaces. It is demonstrated that the improved harmony search algorithm is efficient and effective for the minimization of factors of safety for various difficult problems, and the method of generating the trial failure surfaces can be important in the minimization process.

An improved harmony search minimization algorithm using different slip surface generation methods for slope stability analysis

Most existing three-dimensional (3D) slope stability analysis methods are based on simple extensions of corresponding two-dimensional (2D) methods of analysis and a plane of symmetry or direction of slide is implicitly assumed. In this paper, 3D asymmetric slope stability models based on extensions of Bishop’s simplified, Janbu’s simplified, and Morgenstern–Price’s methods are developed. Under these new formulations, the direction of slide is unique and is determined from 3D force/moment equilibrium. Results from the new formulations are similar to the classical methods in normal cases but are numerically stable under transverse load. Further, the writers demonstrate that the present formulation is actually equivalent to the axes rotation formulation by Jiang and Yamagami but is much more convenient to be used for general problems. The writers have also discovered some inherent limitations of 3D limit equilibrium analysis which are absent in the corresponding 2D analysis.

Yung Ming Cheng

Papers

Location of critical failure surface and some further studies on slope stability analysis

Particle swarm optimization algorithm for the location of the critical non-circular failure surface in two-dimensional slope stability analysis

Performance studies on six heuristic global optimization methods in the location of critical slip surface

An improved harmony search minimization algorithm using different slip surface generation methods for slope stability analysis

Three-Dimensional Asymmetrical Slope Stability Analysis Extension of Bishop’s, Janbu’s, and Morgenstern — Price’s Techniques