Ultimate pit limit optimization plays a major role in the mining industry as it serves as the elementary foundation of all the activities in mine planning. This paper reviews and documents some methods used in ultimate pit limit optimization and gives a clear insight of these algorithms, their functionalities and limitations to open up more research opportunities. The algorithms reviewed are classified as rigorous or heuristic. The Lerchs–Grossman algorithm was found to have wider software application as compared to other algorithms. Genetic algorithm, artificial neural network, pseudoflow and stochastic approach also give great insights to focus in the future.

To study the effects of the number of freezing–thawing cycles (F-T cycles), the dry density, and the average particle diameter on the mechanical properties of tailings, the calibration laws of the fine-scale parameters in the discrete particle element numerical simulation software PFC2D(Particle Flow Code) were first tested, and then pre-experiments were conducted in the form of orthogonal tests. Finally, according to the results of the pre-experiments and the analysis of the pre-experimental results by SPSS (Statistical Product Service Solutions) software, uniaxial tests were carried out for different numbers of freeze–thaw cycles, different dry densities, and different average particle sizes. The tailings specimens were subjected to uniaxial compression simulations. The results showed that (1) the uniaxial compressive strength of the tailings specimens decreased with each freeze–thaw cycle, and stabilized after seven freeze–thaw cycles. (2) With a greater number of freeze–thaw actions, the porosity of the tailings increased after freeze–thawing. The peak of porosity was much higher than that of the models with fewer than seven freeze–thaw actions. (3) The contact number of tailings specimens showed a significant decrease after the number of freeze–thaw cycles reached seven. However, the amount of exposure was not the main factor affecting the strength of tailings (4). As the number of freeze–thaws increased, the tailings model was more prone to stress concentration. Previously, PFC software has been applied to tailings simulation studies, and this study verifies the feasibility of this method. This research is able to offer a reference for studying the mechanical property changes of tailings in the cold highland area.

Changes in the stress field and seepage field of mining unloading are one of the important causes of deformation and destabilization of the rock body of the bottom slab. With the increase of mining intensity and depth, the disaster of water influx on the bottom plate under the dual action of mining unloading and pressurized water has become one of the main problems restricting the efficient and safe mining of coal. Based on the research background of confined water inrush from Ordovician limestone floor in North China Coalfield, the numerical analysis revealed that mining unloading concentrates stresses, increases deformation, and increases the plastic zone and permeability range. Based on laboratory acoustic emission and mechanical tests, it is found that the peak of acoustic emission ringing number can be one of the precursor information of limestone seepage mutation. This study reveals the evolution law of rock body deformation and permeability under the unloading path, and the research obtains the unloading seepage and water gushing disaster mechanism of the subgrade rock body.

Realization of good returns in the mining venture needs careful planning, scheduling, design and optimization of all mining activities which are dependent upon reliable resource estimates. The mineral resource estimation method employed in a deposit thus plays a major role in reduction of risks associated in mining. In this study, indicator kriging, ordinary kriging and inverse distance weighting methods are compared for MonywaKandLdeposits. Correlation coefficients in the regression analysis of downhole composites compared with the ordinary kriging estimates forKandLdeposits were 0.982 and 0.985 respectively, thus selecting it as the best estimator for the two deposits.