Slope stability analysis considering the rotated anisotropy in soil properties

Purpose This paper aims to analyze the influence of rotated anisotropy on the stability of slope, the random finite element method is used in this study. Design/methodology/approach The random field is generated by the discrete cosine transform (DCT) method, which can generate random field with different rotated angles conveniently. Findings Two idealized slopes are analyzed; it is observed that the rotated angle significantly affects the slope failure risk. The two examples support the conclusion that when the orientation of the layers is nearly perpendicular to the slip surface, the slope is in a relative stable condition. The results of heterogeneous slope with two clay layers demonstrate that the rotated angle of lower layer mainly controls the failure mechanism of the slope, and the rotated angle of upper layer exhibits a significant influence on the probability of slope failure. Originality/value The method for rotated anisotropy random field generation based on the DCT has a simple expression with few parameters and is convenient for implementation and practical application. The proposed method and the results obtained are useful for analyzing the stability of the heterogeneous slopes in engineering projects.

GSTools: The Python toolbox for your geo-statistical project!

<p><span>Geo-scientific model development is lacking comprehensive open source tools, that are providing state-of-the art geo-statistic methods. To bridge this gap, we developed </span><span>a</span><span> geo-statistical toolbox named GSTools, which is a Python package providing an </span><span>abundance</span><span> of methods in a modern object oriented approach. Covered </span><span>use-cases</span><span> are:</span></p><ul><li> <p>covariance models (many readily provided and even user-defined models with a lot of functionality)</p> </li> <li> <p>random field generation (multigaussian and in-compressible vector fields)</p> </li> <li> <p>field transformations (boxcox, Zinn and Harvey, log-normal, binary)</p> </li> <li> <p>kriging (simple, ordinary, universal, external drift or detrended)</p> </li> <li> <p>variogram estimation (Cressie and Matheron estimators)</p> </li> <li> <p>I/O routines (interfaces to pyvista and meshio for mesh support)</p> </li> <li> <p>plotting routines (inspect your covariance model or random field on the fly)</p> </li> </ul><p><span>GSTools is developed openly within a GitHub organization </span><span>(</span>https://github.com/GeoStat-Framework<span>). O</span><span>n the one hand to be able to respond to the needs of the modeling community and integrate suggested functionalit</span><span>ies</span><span> and contributions,</span><span> on the other hand to guarantee stability and reliability of the code-base through continuous-integration features provided by the GitHub infrastructure</span><span>.</span></p><p>We will present several applications of the mentioned routines to demonstrate the interface and capabilities of GSTools.</p>

A method of generating a random optical field using the Karhunen-Loeve expansion to simulate atmospheric turbulence

It is proposed to use the random field generation in the numerical simulation of the propagation of radiation through a random medium using method based on the Karhunen–Loeve expansion with various types of correlation operators to describe turbulence simulators. The properties of the calculated simulators of a random medium with a Gaussian correlation function were investigated in modeling the propagation of Laguerre-Gaussian vortex beams. The simulation results showed that an increase in the order of the optical vortex leads, as in the experiment, to lower stability of the phase singularity of the beams to random optical fluctuations. The similarity of the simulation results and the optical experiments indicates the promise of the proposed approach for the synthesis of random environment simulators.

Random field generation of the material properties in the lattice discrete element method

The lattice discrete element method has been successfully used to simulate the evolution of damage in structural mechanics. The approach has led to new perspectives in the solution of fracture problems in nonhomogeneous materials. For such purpose, it is necessary to introduce correctly the parameters that characterize the random nature of the material. In this article, the fracture toughness of the material is considered a three-dimensional random field, characterized by a probability density and the spatial distribution of the simulated random field which is governed by the correlation length. The methodology used to separate the random field simulated from the discretization level used is depicted in detail. Examples are shown that verify the objectivity of the results obtained respecting the discretization levels. Finally, the article concludes by emphasizing the relevance of this implementation in the damage simulation process in the so-called heterogeneous materials.