The precise estimation and forecast of the safety factor (SF) in civil engineering applications is considered as an important issue to reduce engineering risk. The present research investigates new artificial intelligence (AI) techniques for the prediction of SF values of retaining walls, as important and resistant structures for ground forces. These structures have complicated performances in dynamic conditions. Consequently, more than 8000 designs of these structures were dynamically evaluated. Two AI models, namely the imperialist competitive algorithm (ICA)-artificial neural network (ANN), and the genetic algorithm (GA)-ANN were used for the forecasting of SF values. In order to design intelligent models, parameters i.e., the wall thickness, stone density, wall height, soil density, and internal soil friction angle were examined under different dynamic conditions and assigned as inputs to predict SF of retaining walls. Various models of these systems were constructed and compared with each other to obtain the best one. Results of models indicated that although both hybrid models are able to predict SF values with a high accuracy and they can be introduced as new models in the field, the retaining wall performance could be properly predicted in dynamic conditions using the ICA-ANN model. Under these conditions, a combination of engineering design and artificial intelligence techniques can be used to control and secure retaining walls in dynamic conditions.

This experimental investigation was conducted to research the properties of polypropylene (PP) fiber-reinforced cemented paste backfill (CPB). The unconfined compressive strength (UCS) of the fiber-reinforced CPB showed a significant improvement with average UCS increase ratios of 141.07%, 57.62% and 63.17% at 3, 7 and 28 days, respectively. The macroscopic failure mode and SEM analysis indicated that fibers prevented the formation of large tensile and shear cracks during the pull-out and pull-off failure modes. A linear fitting function for the UCS at a curing time of 3 days and two polynomial fitting functions for the UCS at curing times of 7 and 28 days were established to characterize the relationship between the UCS of the fiber-reinforced and unreinforced CPB. Moreover, based on composite mechanics, nonlinear models related to the UCS and fiber reinforcement index were obtained. The estimated functions containing the fiber reinforcement index λ, which consists of the fiber content and aspect ratio of fiber, could evaluate the UCS. Furthermore, the fiber reinforcement index λ quantifies the enhancement by the fibers. Both estimation results indicated that the UCS values were estimated accurately at curing times of 3, 7 and 28 days in this study. Additionally, the estimation models could be used to guide the strength design of fiber-reinforced CPB. Besides this, the results showed that fiber-reinforced CPB can be used more widely in mine backfills and meets the requirements of controlled low-strength material (CLSM) for broader applications.

A 3D numerical model was presented to investigate the blast-induced damage characteristics of highly stressed rock mass. The RHT (Riedel, Hiermaier, and Thoma) model in LS-DYNA was used to simulate the blast-induced damage and its parameters were calibrated by a physical model test. Based on the calibrated numerical model, the influences of confining pressure and free surface span on the blast-induced damage characteristics were investigated. The results show that under uniaxial loading, the crater volume increases with confining pressure increases. The uniaxial static load can change the optimal burden and the critical embedding depth of charge. In stressed rock, the variation law of the crater shape affected by radial tensile fractures is opposite to that affected by reflected tensile fractures. Under the biaxial static load, the crater volume of the borehole placed on the side of the max static load is greater than the other side. The explosion crater can be improved by increasing the free surface span on the same side. Finally, it is suggested that the blasting efficiency can be improved by preferentially detonating the charge on the side of the max static load, and then the charge on the other side can be detonated with a wider free surface span.

A large number of rock works in cold areas suffer from long-term freeze-thaw damage, and it seriously affects the stability of mine slopes. In this paper, the XRD component measurement, P-wave velocity, freeze-thaw cycling test at different times, uniaxial compression test, and scanning electron microscope (SEM) test were carried out to obtain the mechanical properties and microstructure evolution of skarn under the effect of freeze-thaw cycles. The results of the study indicate that with an increase in the number of freeze-thaw cycles, the mass of the rock gradually increases and the P-wave velocity, uniaxial compressive strength, elastic modulus, and Poisson’s ratio all decrease. Based on the SEM image of the rock after crushing, fine pores and fissures gradually developed, expanded, and penetrated each other under the action of freezing and thawing; the inter-particle bonding force decreased; and the cement gradually loosened. The fractal dimension of the specimens under different numbers of freeze-thaw cycles was obtained using the box dimension method, and the degradation of the fine structure of the rock was quantitatively elaborated. By establishing the relationship between the compressive strength of rocks and the fractal dimension, the mechanism of damage to skarn under freeze-thaw action was further investigated. It provides some theoretical basis for the characterization of freeze-thaw damage of rocks in cold regions.