Alkali-activated cementitious materials present an environmentally beneficial and high-performance option in the domain of soil solidification and stabilization. This research focused on granulated blast-furnace slag (GGBFS), a predominant byproduct and solid waste from iron manufacturing that has a limited utilization rate. Due to its high content of calcium (Ca), silicon (Si), and aluminum (Al), slag has emerged as an effective soil curing agent. This study investigated sandy silt by employing alkali-activated slag to examine its solidification and stabilization properties. We assessed the unconfined compressive strength (UCS), deterioration strength, and solidification mechanism of alkali-activated slag-stabilized sandy silt through unconfined compressive strength tests and various microscopic analyses, including X-ray diffraction (XRD), thermogravimetric analysis (TGA), Fourier transform infrared spectroscopy (FITR), and scanning electron microscopy (SEM). These findings indicate that using slag alone for solidifying sandy silt is inefficient. However, following alkali activation, the UCS of solidified soil with sandy silt generally increases with increasing GGBFS content and initially increases, then decreases with increasing alkali-activator content. The ideal proportions of GGBFS and alkali-activator are between 12 %-14 % and 6 %-9 %, respectively. Upon exposure to ordinary and triple-concentration artificial seawater, the strength of the solidified soil generally diminishes over time. It is worth noting that the strength of the samples in group GGBFS14 exhibited an initial increase, followed by a decrease, as the deterioration time increased. With alkali-activator contents of 6 % and 9 %, the strength and durability of the solidified soil remain relatively stable, maintaining robust mechanical properties even after seawater erosion. The resistance of the solidified soil to seawater deterioration increases as the GGBFS content increases. Microscopic tests revealed the presence of amorphous hydration gel products (C-A-S-H). The optimal GGBFS and alkali-activator contents for sandy silt solidification in this study were determined to be 12 %-14 % and 6 %-9 %, respectively. At these optimal levels, the strength of the solidified soil at a curing age of 28 days can reach 13.49 MPa (GGBFS16AA6). This suggests that alkali-activated slag holds potential as a substitute for ordinary Portland cement (OPC) in engineering applications and offers a strategy for reusing GGBFS.

Mechanical tillage before cotton sowing is a crucial process in cotton production. Numerical simulations of soil cutting and energy consumption predictions, along with optimization methods, are very important for understanding the interaction between tillage tools and soil, as well as guiding energy-efficient cultivation practices. The focus of this study is on the problem of cutting sandy silt in Xinjiang cotton fields. Sandy silt can be characterized by its low cohesion and large, loose particles. Starting from the macroscopic physical and mechanical properties of the soil, a soil contact mechanics model considering soil plastic deformation and bonding forces between soil particles is established. By optimizing the cotton field soil discrete element model and parameter calibration methods, the accuracy of the soil cutting simulation is improved. The principles and modelling steps of discrete element method (DEM) simulations for cutting soil are explained in detail, enabling the analysis and evaluation of the complex dynamic behaviour of soil under large deformation conditions and the mechanical properties of the cutting tool. The average error between the energy consumption measured in field rotary tillage experiments and simulation results is 7.04%. By utilizing the simulation results as a dataset, an extreme learning machine (ELM) without a physical model is employed to replace traditional polynomial regression for rapid energy consumption prediction based on the cutting parameters. The average error between the prediction results and simulation results is 4.34%. By using response surface methodology based on the predicted energy consumption, optimal working parameters are determined, resulting in a 10.02% reduction in the power consumption compared to the initial parameter settings. This effectively achieves energy savings in rotary tillage and further validates the accuracy of the simulation method and prediction model.