Quantifying and addressing uncertainties in empirical vibration attenuation relationship for underground blast by re-sampling

Abstract

For efficient and timely execution of deep excavations, tunnelling or mining activities in rock, controlled blasting often becomes essential. For design of the controlled blasting operation, scaled distance regression analysis of trial blast data, namely, distance, charge weight, and peak particle velocity (PPV), is the regular industrial practice. Due to limited number of input data from trial blasts, and further due to variability of underlying media, multiple uncertainties creep into expressions thus developed. To account for these uncertainties in design of safe controlled blasting, therefore, 95 percent confidence expression obtained from trail blast data is generally preferred in industry. However, this approach lacks statistical quantification or treatment of the parameter uncertainty and there is no methodology suggested in literature, codes or standards to address this aspect. The present article proposes to estimate the parameter uncertainties in the empirical vibration attenuation relationship for underground blast using re-sampling approach. With blast data from literature, multiple samples are randomly selected and empirical parameters are evaluated for each set by least square principle. It is found that both empirical parameters in power form of expression (popular in industry) follow Normal distribution. Using the 95 percentile value for each parameter, the safe charges are calculated and thereafter are compared to the traditional industrial practice of employment of 95 percent confidence expression from trail blast data. Re-sampling approach yielded conservative charge weight for lower limiting values (PPV ≤ 15 mm/s) and efficient charge weights for higher limiting values (PPV ≥ 50 mm/s) of PPV.

Ground Motion Prediction of High-Energy Mining Seismic Events: A Bootstrap Approach

“…Energies 2023, 16, x FOR PEER REVIEW 3 of 16 confidence intervals of GMPE parameters for seismic ground vibrations caused by induced seismicity [23], or blasting works [24]. The purpose of this study is to evaluate one of the most important seismic hazard parameters, i.e., the peak ground acceleration (PGA) estimator, which is based on the bootstrapping statistical procedure on the basis of high-energy mining seismicity.…”

“…Another application of bootstrapping in seismology is for determining the uncertainty of estimated seismic deformations [18], determining the confidence intervals of the location of historical earthquakes [19], calculating the horizontal component of the seismic slowness vector [20], calculating the b parameter of the Gutenberg-Richter law [21], as well as estimating the uncertainty of the values describing seismic magnitude attenuation function [22]. There are fewer research studies on the use of bootstrapping to calculate the confidence intervals of GMPE parameters for seismic ground vibrations caused by induced seismicity [23], or blasting works [24].…”

Estimation of Vs30 Bounds From Limited Soil Data Considering Uncertainty

“…The uncertainties in data might be broadly classified as aleatory or epistemic (Tung & Yen, 2005;Coleman & Steele, 2009;Modarres et al, 2010). The aleatory uncertainty is associated with the natural randomness of the process or physical phenomenon and therefore cannot be reduced (Lombardi, 2017;Dauji, 2019). The epistemic uncertainty arises from the deficiencies in information, lack of scientific understanding and inaccuracy in modelling of the physical process and therefore can be reduced with more data and better 171 knowledge of the process (Lombardi, 2017;Dauji, 2019).…”

“…The aleatory uncertainty is associated with the natural randomness of the process or physical phenomenon and therefore cannot be reduced (Lombardi, 2017;Dauji, 2019). The epistemic uncertainty arises from the deficiencies in information, lack of scientific understanding and inaccuracy in modelling of the physical process and therefore can be reduced with more data and better 171 knowledge of the process (Lombardi, 2017;Dauji, 2019). Rather than classification of uncertainties involved in an analysis, the engineering approach is targeted towards estimation of the uncertainty and incorporating the same into the analysis and safe design of the structure.…”

A Re-Look Into Modified Scaled Distance Regression for Prediction of Blast-Induced Ground Vibration

“…A recent study (Murmu et al, 2018) reported application of Monte Carlo simulation for probabilistic study of blast induced ground vibration using empirical relationship. A method for addressing the uncertainty of the empirical attenuation relationship was presented by Dauji (2019) adopting re-sampling approach.…”