In tunnel blasting excavation, it is important to clarify the attenuation law of blast wave propagation and predict the blast vibration velocity effectively to ensure safe tunnel construction and protection design. The effects of the free surface area its quantity on the blast vibration velocity are considered, and free surface parameters are introduced to improve the existing blast vibration velocity prediction formula. Based on the Tianhuan railway Daqianshiling tunnel project, field blast vibration monitoring tests are performed to determine changes in the peak blasting vibration velocity based on the blast distance and free surface area. LS-DYNA is used to establish tunnel blasting excavation models under three operating conditions; subsequently, the attenuation law of blast vibration velocity and changes in the vibration response spectrum are analysed. Results show that the free surface area and number of free surfaces enable the blast vibration velocity to be predicted under various operating conditions: a smaller free surface area results in a narrower frequency band range, whereas more free surfaces result in a narrower frequency band range. The improved blast vibration velocity prediction formula is validated using field and numerical test data. It is indicated that the improved formula is applicable to various tunnelling conditions.
A site experiment is performed herein within a 100 m range using a high-frequency structure activity monitor to explore the impact of different factors on the microseismic source location and analyze the range of influence of the velocity model, number of stations, and array surface on the seismic source location. Moreover, the impact of wave velocity, velocity-free location algorithm, and position of the seismic source on the microseismic location error of mines is discussed by establishing the ideal theoretical model of the wave velocity location and with particle swarm optimization. The impact of the number of stations and tables on the location precision is also explored by using the microseismic signals produced by the artificial seismic source. The results show that, for the location model containing the velocity, the velocity error would greatly affect the location precision, and the velocity-free algorithm receives good location results. The location result is more satisfactory when the seismic source point falls in between array envelope lines. The seismic source location precision is in direct proportion to the number of stations. According to the experiment, within a 100 m range, when the number of stations is over 12, the effect does not significantly grow with the increase of stations; the number of tables affects the location precision; and the multitable location effect is significantly superior to the single-table effect. The research shows that the optimal station density is 0.0192%, and the appropriate sensor layout to form a multitable monitoring network may effectively enhance the microseismic source precision of mines through the selection of a velocity-free location model. On the contrary, the number of stations can be reduced on the premise of the allowable error of the seismic source location, which may effectively reduce the monitoring cost.
This study aims to better understand the energy–frequency characteristics of microseismic wave propagation by monitoring particles in complex geology. Artificial seismic source experiments are conducted using a complex geological model, and variational mode decomposition method is applied to process the microseismic signals, obtain reconstructed microseismic signals and decomposition modes, and calculate the microseismic particle input energy and signal energy at each measurement point. Computations derived from the Sadoff empirical formula are used to evaluate the attenuation of the microseismic particle input energy with the propagation distance. The relationships between microseismic wave center frequency and energy and between the microseismic particle input energy and microseismic signal energy are elucidated. The results show that the microseismic particle input energy follows a power exponential decay trend with increasing propagation distance; the values and distributions of the microseismic particle input energy and signal energy conform to a Gaussian trend in the frequency domain; various geological structures and combinations thereof impose frequency modulation effects on the microseismic wave, where the frequency modulation interval depends on the microseismic waves across the different interfaces; and the linear slope describing the relationship between microseismic particle input energy and signal energy can reflect the microseismic wave propagation state.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.