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使用环保速凝炮泥进行炮孔爆破的实验研究

Experimental investigation of borehole blasting with eco friendly rapid setting gun mud.

作者信息

Zhou Hou-You, Wang Xiao, Gao Zheng-Hua, Zhao Xin, Chi En-An, Zhao Wen-Bo

机构信息

School of Mechanics and Civil Engineering, China University of Mining and Technology-Beijing, Beijing, 100083, China.

School of Materials and Achitectural Engineering (Guizhou School of Emergency Management), Guizhou Normal University, Guiyang, 550025, China.

出版信息

Sci Rep. 2025 Oct 8;15(1):35132. doi: 10.1038/s41598-025-19060-0.

Abstract

To address the challenges of inconvenient material sourcing and low stemming efficiency in horizontal tunnel blasting, this study proposes a novel rapid-setting gun mud. The material's composition, formation mechanism, and initial setting characteristics are first analyzed, and a multi-parameter coupled model for optimal stemming length is established. Subsequently, a series of blasting model tests with varying stemming lengths is conducted, followed by a quantitative analysis of the block-size distribution of limestone under different stemming conditions. The influence of stemming length on rock fragmentation characteristics is revealed, and theoretical predictions are validated against experimental results. Findings indicate that the curing process of the proposed material is primarily driven by hydration reactions, with simple operation, environmental friendliness, and safety for workers. Moreover, the developed multi-parameter coupled model for optimal stemming length shows good agreement with experimental results, providing a quantifiable theoretical basis for the refined parameter design in mechanized tunnel blasting.

摘要

为应对水平巷道爆破中材料采购不便和堵塞效率低下的挑战,本研究提出了一种新型速凝炮泥。首先分析了该材料的组成、形成机理和初凝特性,并建立了最优堵塞长度的多参数耦合模型。随后进行了一系列不同堵塞长度的爆破模型试验,接着对不同堵塞条件下石灰岩的块度分布进行了定量分析。揭示了堵塞长度对岩石破碎特性的影响,并将理论预测结果与实验结果进行了验证。研究结果表明,所提出材料的固化过程主要由水化反应驱动,操作简单、环保且对工人安全。此外,所建立的最优堵塞长度多参数耦合模型与实验结果吻合良好,为机械化巷道爆破的精细化参数设计提供了可量化的理论依据。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/eb3f/12508073/42b48ae93865/41598_2025_19060_Fig1_HTML.jpg

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