Control of Rock Block Fragmentation Based on the Optimization of Shaft Blasting Parameters. (17th December 2020)

• Record Type: Journal Article
• Authors: Li, Qingxiang; Luo, Zhanyou; Huang, Man; Pan, Jiangbo; Wang, Guoshu; Cheng, Yunxin
• Other Names: Lin Hang Academic Editor.
• Is Part Of: Geofluids. Volume 2020(2020)
• Publication Date: 2020-12-17
• Subjects: Hydrogeology -- Periodicals; Sedimentary basins -- Periodicals; Fluids -- Migration -- Periodicals; Groundwater flow -- Periodicals; Geothermal resources -- Periodicals; Fluid dynamics -- Periodicals; Earth -- Crust -- Periodicals; 551.49
• DOI: 10.1155/2020/6687685
• Languages: English
• ISSNs: 1468-8115

Abstract

Abstract : In the construction of shaft, the blockage of the mucking shaft may cause the mud-water inrush disaster. Oversized rock fragmentation is the main cause for the blockage of the mucking shaft in the raise boring machine (RBM) construction method. The influence degree of blasting parameters on rock fragmentation after blasting is quantified by adopting analytic hierarchy process (AHP). On this basis, the shaft blasting maximum rock fragmentation control model based on double hidden layer BP neural network is proposed. Results show that the maximum rock fragmentation discharged from the mucking shaft after blasting should not exceed 1/3 of the diameter of the slag chute. The influence weight of the minimum resistance line that accounts to 15.6%, when AHP is applied for the quantification of the blasting parameters, can be regarded as the most important blasting parameter. The average absolute errors between the predicted value and the actual value of the largest block size control model of the shaft blasting are only 2.6%. The inversion analysis of the model can rapidly obtain the required blasting parameters, which can be used to guide the construction of the tunnel ventilation shaft.