Loess disaster chains on the Heifangtai Platform, China, cause frequent loess landslides and form landslide dams, thus obstructing rivers. In addition, the failure of landslide dams causes loess mudflows and other related disasters. In this study, the influences of different inflow rates on the failure process and triggering mechanisms of loess landslide dams were explored using five sets of model experiments. These experimental results revealed that the failure of loess landslide dams occurs through overtopping and piping failure, or overtopping failure. Overtopping and piping failure can be divided into infiltration, seepage channel development, break overflow, and rebalancing. When the inflow rate was 1.0 L/s, the water could not penetrate the dam in time. Overtopping failure primarily involves horizontal and downward erosion of the breach. The inflow rate was positively correlated with soil transport, peak flow velocity, and peak bulk density based on the experimental data. The bulk density of the failure mudflow was categorized into slow increase, transition, and attenuation stages based on our experimental results. In addition, by analyzing the volume and stability of residual dams, the likelihood and damage degree of secondary hazards after the dam failure were initially explored. This study provides a scientific basis for relevant studies on loess landslide dam failure.

The constitutive model is essential for predicting the deformation and stability of rock-soil mass. The estimation of constitutive model parameters is a necessary and important task for the reliable characterization of mechanical behaviors. However, constitutive model parameters cannot be evaluated accurately with a limited amount of test data, resulting in uncertainty in the prediction of stress-strain curves. This paper proposes a Bayesian analysis framework to address this issue. It combines the Bayesian updating with the structural reliability and adaptive conditional sampling methods to assess the equation parameter of constitutive models. Based on the triaxial and ring shear tests on shear zone soils from the Huangtupo landslide, a statistical damage constitutive model and a critical state hypoplastic constitutive model were used to demonstrate the effectiveness of the proposed framework. Moreover, the parameter uncertainty effects of the damage constitutive model on landslide stability were investigated. Results show that reasonable assessments of the constitutive model parameter can be well realized. The variability of stress-strain curves is strongly related to the model prediction performance. The estimation uncertainty of constitutive model parameters should not be ignored for the landslide stability calculation. Our study provides a reference for uncertainty analysis and parameter assessment of the constitutive model.

This study demonstrates the feasibility of utilizing machine learning (ML) for routine identification of sand particles. Identifying different types of sand is necessary for various geotechnical exploration projects because understanding the specific sand type plays an important role in estimating the physical and mechanical properties of the soil. To accomplish this, dynamic image analysis was employed to generate a substantial volume of sand particle images. Individual size and shape descriptors were automatically extracted from each particle image. The analysis involved use of 40,000 binary particle images representing 20 different sand types, and a corresponding six size and four shape descriptors for each particle (400,000 parameters). Six ML models were trained and tested. The work demonstrates that using size and shape features the models efficiently identified up to 49% of individual sand particles. However, when clusters of particles were considered in conjunction with a voting algorithm, classification accuracy significantly improved to 90%. Among the ML models studied, neural networks performed the best, while decision tree exhibited the lowest accuracy. Finally, the use of size consistently outperformed shape as a classification parameter but combining size and shape parameters yielded superior results across all sands and classifiers. These findings suggest that ML holds much promise for automating sand classification using ordinary images.

This study, using Jinan as a case study, systematically investigates the characteristics and geological genesis of loess-like silty clay in the middle and lower reaches of the Yellow River. The primary distribution of loess-like silty clay is revealed through field surveys, laboratory experiments, and previous literature reviews. The chemical and physical properties of the loess-like silty clay were examined, in addition to investigations into its mineral composition, microstructural characteristics, and engineering mechanical properties, in order to enhance comprehension of its attributes and formation mechanisms. The research suggests that the distinctive soil environment in the area has been influenced by numerous instances of the Yellow River overflow and channel shifts over its history, as well as the impacts of climate change, geological factors, and human activities. The primary sources of material for the loess-like silty clay consist of loess, Hipparion Red Clay, and paleosol layers. The discussion also addresses the impact of regional climate on the formation of mineral components. The aforementioned findings hold significant implications for advancing the understanding of historical climatic and paleogeographic shifts, as well as for addressing engineering challenges associated with the distribution of loess-like silty clay.

Water and sand leakage disasters are likely to occur during construction in water-rich sand layer areas, resulting in ground collapse. The stress-strain action characteristics of discontinuous graded sand under different internal erosion degrees, and the evolution mechanism of water and sand leakage disasters caused by the internal erosion need to be further explored. Therefore, this paper takes the discontinuous graded sand in a water rich sand layer area in Nanchang City of China as the research object. Considering the influence of different fine particle losses (0, 10%, 20% and 30%) under the internal erosion of sand, the salt solution method is used to realize the specified loss of fine particles in the internal erosion. The stress-strain behavior after the loss of fine particles due to internal erosion is studied by triaxial shear test. Meanwhile, the physical model test and PFC-CFD method are both used to study the evolution rules of water and sand leakage disaster considered the influence of internal erosion degrees. Results show that: (1) under the same confining pressure, the peak failure strength of sand samples decreases along with the increase of fine particle loss. (2) In the water and sand leakage test of saturated sand, a natural filter channel is formed above the observed soil arch. The greater the loss of fine particles, the steeper and wider the collapse settlement area. (3) The relationship between the cumulative amount of water and sand leakage and time is nonlinear. The total mass loss of sand increases along with the increase of internal erosion degree. (4) After the soil arch is formed around the damaged opening, the sand continues to converge above the soil arch under the action of water flow, resulting in the dense convergence of contact force chains.

Since 1950, the area of the Shirvan Steppe has been subject to numerous ameliorative measures, as well as the construction of a number of hydrotechnical facilities. Natural and anthropogenic effects have altered the level of groundwater, mineralization level, chemical composition, engineering-geological conditions, soil salinity, and chemical composition of soils. In order to reflect the engineering-geological conditions of the Shirvan Steppe, geological-hydrochemical sections were created in two directions, in the direction of groundwater flow (I-I) and the direction across the flow of groundwater (II-II). The analysis considered the engineering-geological, physical-geographical, geomorphological, geological, and other conditions of the studied area before and after construction of the Upper Shirvan Canal. Along the route of the Upper Shirvan Canal, the research revealed the main soils as follows: loam, clay, gravel-pebble, sand, and loamy sand. The engineering-geological parameters such as minimum moisture capacity, hygroscopic moisture, volume, weight, density, porosity, and granulometric composition of the soils along the route of Ujar, Kurdamir, Goychay regions, and the Upper Shirvan Canal have been determined. Over the 70-year continuous operation of the Upper Shirvan Canal, settlements in the area of its influence expanded, thereby increasing the loading on the canal beyond the norm. As a result of damage to the concrete coatings of the canal, the quality of operation has decreased, some infrastructure located on it has ceased to function, and water losses from the canal have increased. In such conditions, it is important to study the formation of engineering-geological conditions resulting from natural and anthropogenic effects and to take preventive measures against negative impacts. During the reconstruction and subsequent operation of the canal to provide water to the newly irrigated land areas in the Shirvan Steppe, there should be taken into account the technogenic effects on the geological environment and relevant proposals of important scientific and practical importance regarding the reconstruction project.