The Influential Role of Powder Factor vs. Delay in Full-Scale Blasting: A Perspective Through the Fragment Size-Energy Fan

Abstract

The fragmentation of 12 full-scale one-row blasts has been measured by sieving a large portion of the muckpiles. The procedure followed, the difficulties encountered and the solutions adopted to construct the fragment size distribution curves are described in detail; 11 curves were finally constructed as production constraints prevented the required measurements on one of the blasts. The blasts covered a powder factor range between 0.42 and 0.88 kg/m3, and were initiated with two significantly different delays, 4 and 23 ms between holes, to assess the influence of both powder factor and delay on fragmentation. The size distributions are well represented by the Swebrec function, which strongly suggests that the dependence of fragmentation with the powder factor can be analyzed by the fragmentation-energy fan. The result is excellent, and the frag-energy fan model in its simplest form (a four-parameter function) is able to predict sizes between percentage passings 92 to 8% with a mean error of 14.4% and a determination coefficient R2 as high as 0.976. The powder factor above grade has been used, in its energy form obtained as the product of the mass powder factor by the explosive energy per unit mass. The incorporation of six more fragment size distributions, also obtained by sieving in a previous blasting project in the same rock mass, but with different layouts, explosives, delay and blast direction, only reduces R2 to 0.968 and increases the mean error to 15.3%. A strength dependence with the size of the blasted block (burden, bench height, etc.) has been tested for inclusion in the fan formulation, with minor improvement compared with the powder factor alone, as the variation in size of the blasts was very limited. Some size descriptors as in-situ block size and fracture intensity have also been tested, though variations were also limited as all blasts were carried out in the same quarry site, not improving the prediction errors when other blast dimensions (e.g., burden) are used. Incorporating the effect of delay in the fragmentation-energy fan model has been attempted with a cooperation function modifying the powder factor, increasing from instantaneous to an optimum delay value, then decreasing as the delay further increases. The effect of such a function is noticeable in terms of improved prediction; the data analyzed, however, do not allow for a definitive statement on an optimum delay value as calculations with different fan characteristics and data result in different optimum values. The effect of the delay on the fragment size varies with the percentile, from about 10–15% for the high percentiles to somewhat more than 30% for the lower percentiles.

On the Influence of Sampling Scale on the In Situ Block Size Distribution

“…The fragment size distributions of the blasts carried out in each of the twelve bocks characterized were determined by on-site sieving with a mobile screen; the procedure is described and the fragmentation measured is presented in detail and discussed against blast design in a companion paper (Sanchidrián et al 2022). The fragment size distributions are shown in Fig.…”

“…Their impact on the predictions by blast fragmentation models has been tested with the Kuz-Ram (Cunningham 1983(Cunningham , 1987(Cunningham , 2005 and xP-frag (Sanchidrián and Ouchterlony 2017) models. The rock and blasting data employed in the calculation are given in Sanchidrián et al (2022). The results are plotted in Fig.…”

Reduction of Fragment Size from Mining to Mineral Processing: A Review

“…Sanchidrián and Ouchterlony (2017) suggest a relatively long optimum delay time in their xp-frag model. Analysis of fragmentation through the size-energy fan on a set of blasts in a quarry leads to a much shorter optimum delay (Sanchidrián et al 2022). The value of the optimum delay has been a topic of debate in the blasting community that remains a matter of discussion, and so is the amount of size reduction (e.g., from an instantaneous blast) with such an optimum delay.…”

“…This model was developed by Ouchterlony and coworkers (Ouchterlony et al 2017(Ouchterlony et al , 2021Ouchterlony and Sanchidrián 2018;Segarra et al 2018;Sanchidrián et al 2022). Sieving data obtained from tests with different values of specific charge q may be written where x P is the size at the percentage passing P. The exponent = (P) or P is, for a given blast geometry in a given material, a function of P only.…”

Rock fragmentation size distribution control in blasting: a case study of blasting mining in Changjiu Shenshan limestone mine

“…It is essential to note that controlling fragmentation size distribution is a complex issue influenced by multiple factors. Factors such as the physical properties of rocks and geological structures can all impact fragmentation size distribution (Tao et al, 2020;Azizi and Moomivand, 2021;Njock et al, 2021;Sanchidrián et al, 2022). Therefore, in practical applications, it is essential to consider these factors comprehensively and determine the optimal blasting parameters and construction measures through experimental research to achieve effective control over the fragmentation size distribution and fines content.…”