Figure 1.
Distribution of blasting boreholes and the scheme of detonation order.
There are four intervals of blasting, with delayed firing of 25
Table 1.
Main technical characteristics of blasting boreholes at one mine location at “Suva Vrela” quarry. Data recorded at this site are used for surrogate data analysis.*
Figure 2.
Longitudinal, transversal and vertical component of velocity time histories recorded at measuring points MM-1, MM-2 and MM-3.
Table 2.
Recorded ground velocity at three different distances from the blasting source for the borehole distribution given in Figure 1 and Table 1. *
Table 3.
Different conventional predictors.*
Table 4.
Statistical error parameters used for models' evaluation. *
Figure 3.
Surrogate data test for the second null hypothesis.
Zeroth-order prediction error for the ground velocity recordings at the following measuring points: (a) MM-1 (L, T and V), (b) MM-2 (L, T and V), (c) MM-3 (L, T and V). In all the examined cases, ε0>ε, so the null hypothesis cannot be rejected in neither of the examined velocity recordings. Red line denotes the zeroth-order prediction for the original time series (ε0), and black lines denote zeroth-order prediction for the surrogates (ε). Abbreviations L, T and V stand for longitudinal, transversal and vertical component of the recorded ground velocity, respectively.
Figure 4.
Surrogate data test for the third null hypothesis (AAFT).
Zeroth-order prediction error for the ground velocity recordings at the following measuring points: (a) MM-1 (L, T and V), (b) MM-2 (L, T and V), (c) MM-3 (L, T and V). It is clear that ε0>ε for the vertical velocity component at MM-2, and for the longitudinal and transversal velocity component at MM-3, for prediction steps n>4. In all the other cases, ε0<ε, allowing us to reject the null hypothesis. Red line denotes the zeroth-order prediction for the original time series, and black lines denote zeroth-order prediction for the surrogates.
Figure 5.
Surrogate data test for the third null hypothesis (iterated AAFT surrogates).
Zeroth-order prediction error for the ground velocity recordings at the following measuring points: (a) MM-1 (L, T and V), (b) MM-2 (L, T and V), (c) MM-3 (L, T and V). In all the examined cases, except for the vertical velocity component at MM-3, ε0>ε, so the null hypothesis could not be rejected for all of the examined velocity recordings. Red line denotes the zeroth-order prediction for the original time series, and black lines denote zeroth-order prediction for the surrogates.
Figure 6.
Determinism test for velocity recordings at measuring points: a) MM-1, b) MM-2 and c) MM-3.
Squares, circles and triangles denote longitudinal, transversal and vertical component of the velocity, respectively. The values of determinism factor κ are given for the embedding dimension in range m = 2–10. It is evident that κ≤0,81, indicating the absence of deterministic behavior.
Figure 7.
Resultant PPV versus scaled-distance relationship for different conventional predictors: (a) USBM, (b) Langefors-Kihlstrom, (c) General predictor, (d) Ambraseys-Hendron, (e) CMRI.
Note that coefficients A and B for General predictor were determined using multiple regression approach.
Figure 8.
Measured PPV vs. predicted PPV by conventional predictors: (a) USBM, (b) Langefors-Kihlstrom, (c) General predictor, (d) Ambraseys-Hendron, (e) CMRI. It is clear that each of the predictor gives rather low coefficient of determination, in the range R2 = 0.54–0.66.
Table 5.
Calculated values of site constants for conventional predictors.
Table 6.
Input-output parameters for the ANN training and their range.
Figure 9.
Measured PPV vs. predicted PPV by ANN predictor, with high coefficient of determination (R2 = 0.94).
Figure 10.
Global sensitivity analysis of input parameters.
Figure 11.
Comparison of predicted PPV by different predictors. Abbreviations AH, GP and LK stand for Ambraseys-Hendron, General Predictor and Langefors-Kihlstrom, respectively.
Table 7.
Performances of different models for predicting PPV using statistical error parameters given in Table 4.