Vibration prediction with a method based on the absorption property of blast-induced seismic waves: A case study

被引:1
|
作者
Ercins, Serdar [1 ]
机构
[1] Sivas Cumhuriyet Univ, Sivas Tech Sci Vocat Sch, Dept Min & Mineral Extract, TR-58140 Sivas, Turkiye
关键词
blasting; vibration; seismic quality factor; peak particle velocity; scaled distance; ATTENUATION; SURFACE;
D O I
10.1515/geo-2022-0633
中图分类号
P [天文学、地球科学];
学科分类号
07 ;
摘要
In cases where blast vibrations cannot be measured with seismographs, empirical formulas are commonly used to predict vibration by specifying the peak particle velocity (PPV)-scale distance (SD) relationship. A new approach that provides important information about the relationship of seismic waves generated by blasting with rocks is the seismic quality factor (Q). The Q Factor depends on variables such as measurement distance, geological conditions, frequency, and seismic velocity. In this study, the seismic data obtained from blasting were used to determine the Q factor of the field, which in turn determines the Q value of the site. Blast vibrations were calculated using field equations derived from both the conventional and Q-factor methods. The vibration values measured by seismographs were then compared with the calculated data. The Q factor method, which takes into account the frequency content of the seismic waves, the velocity of the surface waves, and the absorption and damping properties of the seismic waves, predicted the vibration velocity with values very close to reality. However, the values obtained using the PPV-SD method are incompatible with the measurement results. The Q method is highly effective in cases where vibration measurement is not feasible. Additionally, the significance of directional changes in predicting blast vibrations is emphasized.
引用
收藏
页数:13
相关论文
共 50 条
  • [31] Propagation characteristics and prediction of blast-induced vibration on closely spaced rock tunnels
    Wang, Xiao
    Li, Jianchun
    Zhao, Xiaobao
    Liang, Yue
    TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY, 2022, 123
  • [32] OPTIMAL POSITIONING OF VIBRATION MONITORING INSTRUMENTS AND THEIR IMPACT ON BLAST-INDUCED SEISMIC INFLUENCE RESULTS
    Stankovic, Sinisa
    Dobrilovic, Mario
    Skrlec, Vinko
    ARCHIVES OF MINING SCIENCES, 2019, 64 (03) : 591 - 607
  • [33] Prediction of Blast-Induced Ground Vibration at a Limestone Quarry: An Artificial Intelligence Approach
    Arthur, Clement Kweku
    Bhatawdekar, Ramesh Murlidhar
    Mohamad, Edy Tonnizam
    Sabri, Mohanad Muayad Sabri
    Bohra, Manish
    Khandelwal, Manoj
    Kwon, Sangki
    APPLIED SCIENCES-BASEL, 2022, 12 (18):
  • [34] Development of a blast-induced vibration prediction model using an artificial neural network
    Das, A.
    Sinha, S.
    Ganguly, S.
    JOURNAL OF THE SOUTHERN AFRICAN INSTITUTE OF MINING AND METALLURGY, 2019, 119 (02) : 187 - 200
  • [35] Prediction of frequency-dependent attenuation of blast-induced vibration in underground excavation
    Zhou, J. R.
    Lu, W. B.
    Zhong, D. W.
    Leng, Z. D.
    Wu, L.
    Yan, P.
    EUROPEAN JOURNAL OF ENVIRONMENTAL AND CIVIL ENGINEERING, 2019, Taylor and Francis Ltd. (25) : 2181 - 2198
  • [36] Energy Generation and Attenuation of Blast-Induced Seismic Waves under In Situ Stress Conditions
    Yang, Jianhua
    Sun, Jinshan
    Jia, Yongsheng
    Yao, Yingkang
    APPLIED SCIENCES-BASEL, 2022, 12 (18):
  • [37] Numerical simulation on radiation and energy of blast-induced seismic waves in deep rock masses
    Yang, Jian-hua
    Wu, Ze-nan
    Sun, Wen-bin
    Yao, Chi
    Wang, Qiu-hui
    JOURNAL OF CENTRAL SOUTH UNIVERSITY, 2022, 29 (02) : 645 - 662
  • [38] Neural network approach based on a bilevel optimization for the prediction of underground blast-induced ground vibration amplitudes
    Gustavo Paneiro
    Fernando O. Durão
    Matilde Costa e Silva
    Pedro A. Bernardo
    Neural Computing and Applications, 2020, 32 : 5975 - 5987
  • [39] Prediction of Blast-Induced Ground Vibration Using an Adaptive Network-Based Fuzzy Inference System
    Jelusic, Primoz
    Ivanic, Andrej
    Lubej, Samo
    APPLIED SCIENCES-BASEL, 2021, 11 (01): : 1 - 15
  • [40] Neural network approach based on a bilevel optimization for the prediction of underground blast-induced ground vibration amplitudes
    Paneiro, Gustavo
    Durao, Fernando O.
    Costa e Silva, Matilde
    Bernardo, Pedro A.
    NEURAL COMPUTING & APPLICATIONS, 2020, 32 (10): : 5975 - 5987