Selection of Blasting Design Parameters Affecting Peak Particle Velocity—a Case Study - Mining, Metallurgy & Exploration (2021)

The present study has been conducted in surface limestone mine to select the controllable blasting design parameters affecting the peak particle velocity (PPV) for assessment of ground vibration. The study aims at using two prominent statistical tools, namely, principal component analysis (PCA) and stepwise selection and elimination (SSE) techniques for identifying the key controllable parameters affecting the PPV. For determining the correlation coefficient between blasting design parameters and PPV from 44 field scale trial blasts, multi-variate linear regression (MLR) technique was done. It was found that the PCA and SSE eliminated a huge number of controllable parameters to identify the most important parameters, affecting the PPV. The PCA eliminated 6 number of parameters while SSE eliminated 5 number of parameters, and the coefficients of determination (R2) obtained were 0.616 and 0.584 for PCA and SSE respectively. The predictor equations were evolved, and these equations were used to validate the PPV results for another set of 21 field scale trial blasts. The predictor equations have been found to be fairly accurate in predicting the PPV values. Further, the PCA technique provides very near prediction of PPV with high degree of correlation in comparison to SSE technique. The paper highlights the role of state-of-art statistical tools in selecting the blasting design parameters affecting the PPV in field-scale blasting.