分类： 矿山工程技术 >> 矿山地质学 提交时间： 2025-07-17
摘要： The utilization of high‑performance ester materials in addressing soil erosion and conserving water remains a crucial area of research in soil remediation. Currently, however, the mechanism underlying the role of these materials in vegetation restoration remains unclear, hampering the accurate determination of the optimal ratio of high‑performance ester composite materials for soil enhancement. To address this issue, this study examines the mechanism of how high‑performance ester composite materials affect the germination and growth of plant seeds through soilless cultivation experiments. The results revealed that the high‑performance ester composite materials significantly enhanced seed germination ability and fostered plant seedling growth. Notably, the promotional effects of the ester adhesive and water‑retaining materials within the high‑performance ester composite varied. Specifically, the adhesive material significantly spurred radicle development, while the water‑retaining material significantly accelerated germ growth. Varying concentrations of adhesive materials exerted distinct effects on plant growth. In particular, a small amount of adhesive materials enhanced seed germination, whereas excessive amounts exhibited inhibitory effects. Consequently, the optimal adhesive materials dosage conducive to plant growth and the optimal weight ratio of adhesive to water‑retaining materials were ascertained. Additionally, the underlying mechanism of high‑performance ester composite materials influence plant growth was elucidated. Overall, this research offers a theoretical foundation for the optimal ratio adjustment of high‑performance ester composite materials to optimize soil improvement efforts.
分类： 矿山工程技术 >> 矿山地质学 提交时间： 2025-07-17
摘要： Prior research on excavation in dense karst cave foundation pits has primarily concentrated on evaluating the localized spatio-temporal influence and isolated geological factors. Nonetheless, this approach oversimplifies modeling conditions, thereby limiting its ability to provide a comprehensive understanding of the vertical displacement field. Consequently, this oversimplification can inflate the safety factor and increase project costs. Therefore, we propose a feedforward neural network (FNN), updated with the loop nested optimal iterative method (LNOIM), which incorporates the spatiotemporal characteristics of monitoring points and geological factors to analyze the engineering sensitivity of karst caves. Ultimately, the global foundation pit vertical displacement field was obtained. Our method has been demonstrated to be effective in a foundation pit in South China ((P value) P > 0.050, Cohen’s d < 0.200). Furthermore, it has been validated in other cases ((Root Mean Square Error) RMSE = 1.576–2.916). This work provides a new perspective on the accurate reflection of the global vertical displacement state of a foundation pit. Additionally, it enhances the ability to sensitively identify caves in dense karst cave areas, thereby improving the safety of foundation pit works.
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