To solve the issues of insufficient early strength of cement stabilized soil and high resource cost, high reduction cost, and high environmental cost induced by the application of cement, the slag and fly ash-based geopolymer was adopted as the stabilizer to treat riverside soft soil. This study mainly investigated the effects of stabilizer content, slag-to-fly ash ratio, and alkaline activator content on the strength of geopolymer stabilized soils with different curing ages. Unconfined compressive strength (UCS), scanning electron microscope (SEM), and X-ray energy spectrum analysis (EDS) tests were carried out. The results show that the stabilizer content, slag–fly ash ratio, and alkaline activator content have a decisive influence on the UCS of geopolymer-stabilized soil. The mix-proportions scheme of geopolymer stabilized riverside soft soil, with a geopolymer content of 15%, a slag–fly ash ratio of 80:20, and an alkaline activator content of 30%, is considered optimum. It is proven by SEM that the uniformly distributed gelatinous products formed in the geopolymer-stabilized soil bind the soil particles tightly. Moreover, the EDS analysis confirms that the gelatinous products are mainly composed of C-S-H gel and sodium-based aluminosilicate (N-A-S-H).
The compaction density of sand-gravel materials has a strong gradation correlation, mainly affected by some material source parameters such as P5 content (material proportion with particle size greater than 5 mm), maximum particle size and curvature coefficient. When evaluating the compaction density of sand-gravel materials, the existing compaction density evaluation models have poor robustness and adaptability because they do not take into full consideration the impact of material source parameters. To overcome the shortcomings of existing compaction density models, this study comprehensively considers the impact of material source parameters and compaction parameters on compaction density. Firstly, asymmetric data were fused and a multi-source heterogeneous dataset was established for compaction density analysis. Then, the Elman neural network optimized by the adaptive simulated annealing particle swarm optimization algorithm was proposed to establish the compaction density evaluation model. Finally, a case study of the Dashimen water conservancy project in China is employed to demonstrate the effectiveness and feasibility of the proposed method. The results show that this model performs high-precision evaluation of the compaction density at any position of the entire working area which can timely correct the weak area of compaction density on the spot, and reduce the number of test pit tests.
Rock mass failure caused by jointed plane is the common disaster in geotechnical engineering. Research on shearing property of jointed rock mass with prestressed anchor bolt and its mechanical property is an aspect for the stability analysis of rock slope and tunnel. This paper studies the stress and deformation of bolt and jointed plane, as well as anchored body and rock mass during shearing by indoor model testing and theoretical analysis. The shearing strength and mechanical property of anchored jointed plane have been systematically studied, and the additional force caused by deformation of prestressed anchor bolt and jointed rock mass during the shearing has been proposed and verified. The anchorage interaction between rock mass and bolt is revealed.
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