The soil in the northwest loess irrigation area has been affected by the dual effects of dry-wet cycling and salt pollution, leading to significant deterioration of the loess properties in this region. Taking Q₃ loess contaminated by Na₂SO₄ as the research object, direct shear tests and scanning electron microscopy (SEM) are used to analyse the changes in mechanical properties and microstructure characteristics after different numbers of dry-wet cycles. The results show that: Under the dual effects of dry-wet cycling and salt pollution, the strength of the loess deteriorates significantly, and the microstructure changes significantly. Among them, the cohesion shows obvious deterioration, with a decline rate of up to 38.24% to 51.4%. With the increase of salt pollution and dry-wet cycling times, the proportion of individual particles in the loess body increases significantly, and the aggregates begin to disintegrate; Na₂SO₄ repeatedly crystallizes and dissolves during dry-wet cycling, thereby exerting a combined effect of salt swelling and salt erosion on the soil; among the two effects, the destructive effect of dry-wet cycling on the soil structure is greater than that of salt pollution. The research results provide an effective reference for engineering activities and pollution control in loess areas.

Clustering of rock discontinuities is crucial for evaluating rock mass stability. The conventional clustering methods often rely on the orientations of rock discontinuities, without considering the influence of physical characteristics on rock mass stability. To address the limitations of single-factor grouping, a stepwise clustering method of rock discontinuities dominated by multivariate parameters based on student-distributed stochastic neighbor embedding (t-SNE) is proposed. This method takes into account the effects of dip direction, dip angle, trace length, opening, filling state and roughness of rock discontinuities. Firstly, the t-SNE algorithm is used to reduce the dimensionality of discontinuity characteristics except for the orientations. Subsequently, the simulated annealing algorithm is employed to search for the global optimal initial values of the K-means algorithm, and the stepwise clustering idea is utilized to accomplish the clustering. The research shows that the proposed method addresses the sparsity issue of high-dimensional data while preserving the local and global structures of the data. Compared to the conventional methods, the proposed method achieves more accurate partitioning of physical characteristics within the spatial distribution similarity zone, resulting in higher grouping accuracy. Furthermore, the proposed method effectively distinguishes the differences between orientations and physical characteristic parameters on rock mass stability without the need for complex weight value calculations. Finally, the proposed method is applied to the measured data of rock discontinuities in an open-pit slope in Xinjiang, China. The grouping results are found to be reasonable and reliable, which further validates the effectiveness of the proposed method in practical engineering. This research provides a reference for stepwise clustering of multi-parameter rock discontinuities.

Statistical analysis and clustering of discontinuities existing in rock mass are the basis of rock mass engineering stability analysis. Considering that the mechanical and hydraulic properties of discontinuities are affected by many factors such as occurrence, trace length, opening, roughness, and filling state. A multi-parameter dominant grouping method of rock mass discontinuities based on principal component analysis is proposed. Firstly, the principal component analysis method is used to select the criterion of the dominant grouping and calculate the weight value of its participation in similarity measurement. Secondly, the global optimal initial clustering center of the fuzzy C-means clustering algorithm is searched using the annealing genetic algorithm. Lastly, the objective function is established by minimizing the weighted sum of the distance between the discontinuities to be grouped and the clustering center, achieving the dominant grouping of multi-parameter rock mass discontinuity. The 200 discontinuities simulated by the computer are divided into dominant groups using the multi-parameter method and compared with other methods. The results show that this method has higher grouping accuracy. The method is applied to the multi-parameter dominant grouping of the measured discontinuities of Huayang Tunnel of Chongqing Third Ring Expressway. The grouping results are reasonable and reliable, which further verify that the method has significant engineering application value.