Determination and stability analysis of ultimate open-pit slope under geomechanical uncertainty

In open-pit mines,pit slope as one of the important parameters affects the mine economy and total minable reserve,and it is also affected by different uncertainties which arising from many sources.One of the most critical sources of uncertainty effects on the pit slope design is rock mass geomechanical properties.By comparing the probability of failure resulted from deterministic procedure and probabilistic one,this paper investigated the effects of aforesaid uncertainties on open-pit slope stability in metal mines.In this way,to reduce the effect of variance,it implemented Latin Hypercube Sampling(LHS)technique.Furthermore,a hypothesis test was exerted to compare the effects on two cases in Middle East.Subsequently,the investigation approved high influence of geomechanical uncertainties on overall pit steepness and stability in both iron and copper mines,though on the first case the effects were just over.

A back-propagation neural-network-based displacement back analysis for the identification of the geomechanical parameters of the Yonglang landslide in China

Xigeda formation is a type of hundredmeter-thick lacustrine sediments of being prone to triggering landslides along the trunk channel and tributaries of the upper Yangtze River in China. The Yonglang landslide located near Yonglang Town of Dechang County in Sichuan Province of China, which was a typical Xigeda formation landslide, was stabilized by anti-slide piles. Loading tests on a loading-test pile were conducted to measure the displacements and moments. The uncertainty of the tested geomechanical parameters of the Yonglang landslide over certain ranges would be problematic during the evaluation of the landslide. Thus, uniform design was introduced in the experimental design,and by which, numerical analyses of the loading-test pile were performed using Fast Lagrangian Analysis of Continua(FLAC3D) to acquire a database of the geomechanical parameters of the Yonglang landslide and the corresponding displacements of the loadingtest pile. A three-layer back-propagation neural network was established and trained with the database, and then tested and verified for its accuracy and reliability in numerical simulations. Displacement back analysis was conducted by substituting the displacements of the loading-test pile to the well-trained three-layer back-propagation neural network so as to identify the geomechanical parameters of the Yonglang landslide. The neuralnetwork-based displacement back analysis method with the proposed methodology is verified to be accurate and reliable for the identification of the uncertain geomechanical parameters of landslides.

A comprehensive geomechanical method for the assessment of rockburst hazards in underground mining

Rockburst hazard in mining industry all over the world is one of the most severe hazards. It is becoming increasingly common because of the ever-growing depths of mining operations accompanied by the increasing strength of rocks. One of the most difficult issues is to predict this hazard before the mining operations, whether geophysical investigations have been conducted or not. Polish experience in this field shows that in such cases an effective solution can be the geomechanical method. Therefore, extensive studies on rockburst hazard should focus on three main aspects:(1) rock mass and rock(and coal)predisposition to rockburst–laboratory tests and empirical analyses based on lithology,(2) identification of the potential places with stress and elastic energy concentration in the rock mass within the area planned for exploitation, and(3) the assessment of the impact of mining tremors on the surface. This preliminary geomechanical analysis assesses the propensity of the rock mass to dynamic breakage and provides quantitatively the level of rockburst hazard. The paper presents Polish experience in rockburst hazard assessment with the use of geomechanical method, as well as some solutions and examples of such analyses.