Rock slope stability analyses using extreme learning neural network and terminal steepest descent algorithm

The analysis of rock slope stability is a classical problem for geotechnical engineers. However, for practicing engineers, proper software is not usually user friendly, and additional resources capable of providing information useful for decision-making are required. This study developed a convenient tool that can provide a prompt assessment of rock slope stability. A nonlinear input–output mapping of the rock slope system was constructed using a neural network trained by an extreme learning algorithm. The training data was obtained by using finite element upper and lower bound limit analysis methods. The newly developed techniques in this study can either estimate the factor of safety for a rock slope or obtain the implicit parameters through back analyses. Back analysis parameter identification was performed using a terminal steepest descent algorithm based on the finite-time stability theory. This algorithm not only guarantees finite-time error convergence but also achieves exact zero convergence, unlike the conventional steepest descent algorithm in which the training error never reaches zero

Application of neural network to rock slope stability assessments

It is known that rock masses are inhomogeneous, discontinuous media composed of rock material and naturally occurring discontinuities such as joints, fractures and bedding planes. These features make any analysis very difficult using simple theoretical solutions. Generally speaking, back analysis technique can be used to capture some implicit parameters for geotechnical problems. In order to perform back analyses, the procedure of trial and error is generally required. However, it would be time-consuming. This study aims at applying a neural network to do the back analysis for rock slope failures. The neural network tool will be trained by using the solutions of finite element upper and lower bound limit analysis methods. Therefore, the uncertain parameter can be obtained, particularly for rock mass disturbanc

Effect of various types of removable appliances and dental implants on the oral microbiocenosis during orthopedic treatment

The problem of complications arising after dental implantation is still relevant. The aim of the work was to investigate the effect of various types of removable appliances and dental implants on the oral microbiocenosis during orthopedic treatment of 64 people: 12 patients of the first index group, 40 patients of the second index group and 12 people of the control group. 6 months after the implants were installed, as a result of a microbiological study of the oral cavity, the differences were found in the qualitative composition of the microflora of the mucous membrane around the neck of the dental implant. In the first index group representatives of normal microflora prevailed. In 100% of cases Streptococcus vestibularis was isolated, from more than half patients S. oralis, S. mitis, Rothia mucilaginosa were isolated, S. gordonii was isolated from one patient. In the second index group, a significant diversity of microbial species was observed, including enterobacteria, which were isolated from 22.5% of the examined patients. In the control group, in addition to representatives of the normal microflora of the oral mucosa S. vestibularis (75.5%), S. oralis (50.0%), Neisseria subflava (66.7%) and Haemophylus parainfluenzae (50.0%) were found. From all patients of the control groups S. gordonii was isolated, as well as the other potentially pathogenic streptococci species, S. anginosus and S. constellatus by 66.7%. The type of removable appliances and dental implants used affects the microflora composition of the oral cavity, and, consequently, the further prognosis and the risk of complications. Collapsible dental implant supported removable prosthetic appliances with a metal frame and fixing elements, telescopic crowns and clasps less than other types of prosthetic appliances change the qualitative composition of the microflora of the oral mucosa around the neck of the dental implant.</jats:p

Limit Analysis of Complex 3D Steel Structures Using Second-Order Cone Programming

International audienceThe modelling of complex steel structures under static loading using rigid perfectly plastic material is presented within the framework of second-order cone programming (SOCP). The classic upper and lower bound principles of yield analysis, naturally written as optimization problems, are formulated as a pair of dual second-order cone programs which are then solved using a state-of-the art primal-dual interior point method (IPM). The IPM shows good robustness and efficiency along with reduced computational times especially for limit analysis. The whole process is illustrated first with basic steel structures checks of fillet welds or beams under biaxial bending moment, and second with complex 3D steel assemblies. The results show good agreement with the failures modes and resistance values presented in the Eurocode and allows us to obtain a reliable estimate of the ultimate resistance within a reasonable time