Multivariate statistical analysis approach for prediction of blast-induced ground vibration

被引:0
作者
Vivek K. Himanshu
M. P. Roy
A. K. Mishra
Ranjit Kumar Paswan
Deepak Panda
P. K. Singh
机构
[1] CSIR - Central Institute of Mining & Fuel Research,
[2] Indian Institute of Technology,undefined
[3] Indian School of Mines,undefined
[4] National Institute of Technology Rourkela,undefined
来源
Arabian Journal of Geosciences | 2018年 / 11卷
关键词
Peak particle velocity; Multivariate regression; Multiple coefficient of correlation; Blast design parameters; Blast-induced ground vibration;
D O I
暂无
中图分类号
学科分类号
摘要
Excavation of coal, overburden, and mineral deposits by blasting is dominant over the globe to date, although there are certain undesirable effects of blasting which need to be controlled. Blast-induced vibration is one of the major concerns for blast designers as it may lead to structural damage. The empirical method for prediction of blast-induced vibration has been adopted by many researchers in the form of predictor equations. Predictor equations are site specific and indirectly related to physicomechanical and geological properties of rock mass as blast-induced ground vibration is a function of various controllable and uncontrollable parameters. Rock parameters for blasting face and propagation media for blast vibration waves are uncontrollable parameters, whereas blast design parameters like hole diameter, hole depth, column length of explosive charge, total number of blast holes, burden, spacing, explosive charge per delay, total explosive charge in a blasting round, and initiation system are controllable parameters. Optimization of blast design parameters is based on site condition and availability of equipment. Most of the smaller mines have predesigned blasting parameters except explosive charge per delay, total explosive charge, and distance of blast face from surface structures. However, larger opencast mines have variations in blast design parameters for different benches based on strata condition: Multivariate predictor equation is necessary in such case. This paper deals with a case study to establish multivariate predictor equation for Moher and Moher Amlohri Extension opencast mine of India. The multivariate statistical regression approach to establish linear and logarithmic scale relation between variables to predict peak particle velocity (PPV) has been used for this purpose. Blast design has been proposed based on established multivariate regression equation to optimize blast design parameters keeping PPV within legislative limits.
引用
收藏
相关论文
共 34 条
[1]  
Athanasopoulous GA(2000)Ground vibrations from sheetpile driving in urban environment: measurements, analysis and effects on buildings and occupants Soil Dyn Earthq Eng 19 371-387
[2]  
Pelekis PC(2012)Complexity analysis of blast-induced vibrations in underground mining: a case study Min Sci Technol 22 125-131
[3]  
Cardu M(2015)Investigating the effects of bench geometry and delay times on the blast induced vibrations in an open-pit quarry GEAM 1 45-56
[4]  
Dompieri M(2009)An assessment of blasting vibrations: a case study on quarry operation Am J Environ Sci 5 468-474
[5]  
Seccatore J(2001)Prediction of particle velocity caused by blasting for an infrastructure excavation covering granite bedrock Miner Resour Eng 10 205-218
[6]  
Cardu M(2002)Analysis of ground vibrations caused by bench blasting at can open-pit lignite mine in Turkey Environ Geol 41 653-661
[7]  
Mucci A(2012)Response of foundations subjected to blast loadings: state of the art review Disaster Advances 5 54-63
[8]  
Uyar G(2008)The importance of site-specific characters in prediction models for blast-induced ground vibrations Soil Dyn Earthq Eng 28 405-414
[9]  
Giraudi A(2010)Predicting blast- induced ground vibration using various types of neural networks Soil Dyn Earthq Eng 30 1233-1236
[10]  
Cardu M(2011)Prediction of blast-induced ground vibration using artificial neural networks Tunn Undergr Space Technol 26 46-50