Effective methods for extending the storage capacity of tailings for a mining company include expanding and increasing the height of the tailings dam. However, this change could lead to an uplift in the phreatic line and a decrease in the slope stability. In this paper, a new drainage system combining a horizontal drainage pipe with an upward bending slotted pipe was proposed and applied to the design of a seepage-proof system for the Xigou tailings dam with an increased height. To accurately simulate the performance of the seepage control system, a three-dimensional finite element model was established on the basis of a geological investigation of the site conditions. In this work, a substructure technique was used to model the drainage pipe with a small radius and dense spacing to reduce the difficulty in mesh generation, and a back-analysis method called MPSO-BP (modified particle swarm optimization algorithm and a back propagation neural network) was used to correct the measured permeability coefficients. The results show that the new drainage system can effectively dissipate the seepage pressure, decrease the phreatic surface, and improve the safety factors of the slope stability. The proposed drainage system can also meet the seepage stability requirements of the higher tailings dam. Additionally, this system can be widely deployed in similar projects.

The concrete–rock interfacial transition zone (ITZ) is generally considered the weak layer in hydraulic engineering, for it is more permeable than the intact concrete or rocks. The water permeability of the ITZ is a critical parameter concerned with structural safety and durability. However, the permeability and pore structure of the ITZ has not been investigated previously, and the mathematical model of ITZ permeability has not been established. This study performed multi-scale experiments on the concrete–rock ITZ with various rock types (limestone, granite, and sandstone). A series of quantitative and qualitative analysis techniques, including NMR, SEM-EDS, and XRD, characterize the ITZ pore structures. The controlled constant flow method was used to determine the permeability of the concrete, rock, and ITZ. The mathematical model of ITZ permeability was proposed using the fractal theory. The consistency between the experimental data and the proposed model indicates the reliability of this study. The results of the experiment show that ITZ permeability is between 4.08 × 10⁻¹⁸ m² and 5.74 × 10⁻¹⁸ m². The results of the experiment and the proposed model could determine ITZ permeability in hydraulic structure safety and durability analysis.

Back analysis for seepage parameters is a classic issue in hydraulic engineering seepage calculations. Considering the characteristics of inversion problems, including high dimensionality, numerous local optimal values, poor convergence performance, and excessive calculation time, a biological immune mechanism-based quantum particle swarm optimization (IQPSO) algorithm was proposed to solve the inversion problem. By introducing a concentration regulation strategy to improve the population diversity and a vaccination strategy to accelerate the convergence rate, the modified algorithm overcame the shortcomings of traditional PSO which can easily fall into a local optimum. Furthermore, a simple multicore parallel computation strategy was applied to reduce computation time. The effectiveness and practicability of IQPSO were evaluated by numerical experiments. In this paper, taking one concrete face rock-fill dam (CFRD) as a case, a back analysis for seepage parameters was accomplished by utilizing the proposed optimization algorithm and the steady seepage field of the dam was analysed by the finite element method (FEM). Compared with immune PSO and quantum PSO, the proposed algorithm had better global search ability, convergence performance, and calculation rate. The optimized back analysis could obtain the permeability coefficient of CFRD with high accuracy.

The calcium leaching effect leads to a decrease in the impermeability of the impervious curtain. The inverse analysis strategy was introduced in this study because the calcium leaching parameters of the curtain are not easy to determine. An orthogonal design and the finite element method were used in the strategy. The time-series data of hydraulic head and leakage volume were applied to construct the objective function. The extreme learning machine (ELM) was proposed to build the reflection sets. Genetic algorithm (GA), simulated annealing (SA), sparrow search algorithm (SSA), and particle swarm optimization (PSO) were employed to accelerate the iterative search for the target parameters. The target parameters of the calcium leaching model were used for finite element verification by comparing the monitored and simulated values. The simulated values of hydraulic head and leakage by PSO show good agreement with measurements. The evolution of the curtain permeability coefficient in 100 years was analyzed. The results demonstrate the strategy’s feasibility in determining the curtain’s calcium leaching parameters and permeability coefficients.