The spatial variability in rock mass mechanical parameters critically affects slope stability assessments. This study investigated the southern slope of the Bayan Obo open-pit mine. A representative elementary volume (REV) with a side length of 14 m was determined through discrete fracture network (DFN) simulations. Based on the rock quality designation (RQD) data from 40 boreholes, a three-dimensional spatial distribution model of the RQD was constructed using Ordinary Kriging interpolation. The RQD values were converted into geological strength index (GSI) values through an empirical correlation, and the generalized Hoek–Brown criterion was applied to develop a spatially heterogeneous equivalent mechanical parameter field. Numerical simulations were performed using FLAC3D, with the slope stability evaluated using the point safety factor (PSF) method. For comparison, three homogeneous benchmark models based on the 5th, 25th, and 50th percentiles produced profile-scale safety factors of 0.96–1.92 and failed to replicate the observed failure geometry. By contrast, the heterogeneous model yielded safety factors of approximately 1.03–1.08 and accurately reproduced the mapped sliding surface. These findings demonstrate that incorporating spatial heterogeneity significantly improves the accuracy of slope stability assessments, providing a robust theoretical basis for targeted monitoring and reinforcement design.

This paper examines the applicability of four failure criteria applied to layered rocks, namely, Pariseau’s model, linear empirical equation, nonlinear empirical equation (LEE and NLEE), and Jaeger’s plane‐of‐weakness model (JPW). A database comprising 282 uniaxial compressive strength (UCS) tests and 1,273 triaxial tests conducted worldwide on layered rocks is compiled. Pariseau’s model is classified as a continuous function, and LEE and NLEE, as well as JPW, are classified as piecewise functions. Nonlinear least squares and traversing methods are used to determine the global minima of the material coefficients in the two types of functions. The goodness of fit of these criteria for the database is evaluated. Two statistical parameters, namely, regression coefficient (R²) and mean absolute percentage error (MAPE) are used for precision assessment. The aforementioned methods and the criteria are further used for evaluating the surrounding rock stability of the eastern slope of Yanshan iron open‐pit and the underground powerhouse of the Jinping I hydropower station. The results show that (1) Pariseau’s model is not suitable for layered rocks when n = 2, and the fit is worst in the condition of insufficient triaxial data when n = 1; (2) the MAPE of the empirical equation (LEE and NLEE) is within 20%, with the best predictive accuracy under medium to low confining pressures, and the MPAE of JPW is within 40%, with the best predictive accuracy under high confining pressures; and (3) calculation of the damage area of the slope and underground powerhouse and comparison with the actual damage on the site verify that the empirical equation has the best engineering prediction accuracy under medium to low confining pressure conditions.

Coal price may vary significantly within a given coalseam, andthe accurate characterization of coal price plays an important rolein the rational development and utilization of coal resources. A geostatistics-block-basedmethod is proposed to obtain the spatial correlation of borehole surveydata and map the heterogenous distribution of coal seam thicknessand coal quality (including calorific value, volatile content, ashcontent, and sulfur content). A block model of thermal coal priceis next established considering the spatial distribution of coal qualityparameters. Taking an undisclosed coal mine as an example, the estimationprocess of coal price block model is described in detail, and themining sequence among several panels is optimized considering theheterogenous coal price. The coal price ranges from 814 to 1671 ChineseYuan/t within the research area, and the net present value is increasedby 1.53% after the optimization of the mining sequence. The resultindicated that the coal price is generally heterogenous in a coalseam, and it has a significant influence on the mining sequence. Theaccurate modeling of coal seam properties has wide applications inmining engineering.