## 5 Results and Discussion
### Simulation of Flyrock Trajectories  
In addition to blast design variables, flyrock is dependent on a range of uncontrollable factors, including the presence of discontinuities and other rock mass characteristics such as fissures and cracks. As a result, its occurrence remains unpredictable until the blast is executed. Therefore, a projectile simulation was carried out by utilizing \(\gamma\)/ prediction results on the testing dataset. In the experiment, the flight trajectories for the probable occurrence of flyrock were forecasted considering different possible launch circumstances. To ensure a conservative estimation for delimiting the danger zone at the investigated sites, the upper limit of Cl\({}_{0.95}\) for the predicted velocity was considered. Based on the principles of projectile motion, it was hypothesized that a flying fragment would reach its maximum range at an angle of 45\({}^{\circ}\). Therefore, the same launch angle measure was used consistently throughout the simulations. The largest flyrock fragment observed in all the blasts had a mean diameter of 22 cm, so assuming a spherical shape, five different diameters of flyrock in the range of 5-25 cm were considered for simulation, and their corresponding masses were calculated following the approach suggested by [PERSON] et al. [23]. For launch locations, both the bench top and bench face were considered, as cratering and rifling occur from the bench top, while face bursting occurs at the bench face. Consequently, the projectile simulations were conducted using fifteen unique combinations of five distinct fragment masses and three evenly spaced launch locations on the bench face measuring upwards from the toe. Table 8 details the specifics of the experimental data utilized for simulation and it contains a single entry as an example for demonstrating the experiment in this article. The drag coefficient was taken to be 0.08, and the acceleration due to gravity was set as 9.8 m/s\({}^{2}\). The trajectories resulting from simulations for the 15 different combinations are depicted in Figure 17, showcasing the range and patterns of flyrock trajectories for one of the instances from Mine D as given in Table 8. The farthest range of flyrock for this particular  
Figure 16: Simple graphical user interface created for using the EETR-BO model to predict \(\gamma_{f}\). \begin{table}
\begin{tabular}{c c c c c c c c c c c} \hline \hline \multirow{3}{*}{**Mine**} & \multirow{3}{*}{\
\begin{tabular}{c} \(\rho_{r}\) \\ **(g/cc)** \\ **Predicted** \(\gamma_{f}\) **(m/s)** \\ \end{tabular} } & \multirow{3}{*}{
\begin{tabular}{c} **Upper Limit of** \\ **the Cl\({}_{0.95}\) of** \\ **Predicted** \(\gamma_{f}\) **(m/s)** \\ \end{tabular} } & \multicolumn{3}{c}{**Lanch Locations Marked at Three**} & \multicolumn{3}{c}{**Mass of Flying Fragments Considered for the Simulation**} \\  & & & **Different Point Measuring Heights (in m)** & & & & **Experiment (in kg)** & \\ \cline{3-10}  & & & & **Upwards from the Toe** & & & & & & \\ \cline{3-10}  & & & **Location I** & **Location II** & **Location III** & **I** & **II** & **III** & **IV** & **V** \\ \hline D & 4.39 & 38.42 & 9.00 & 7.50 & 3.75 & 0.29 & 2.30 & 7.76 & 18.39 & 35.91 \\ \hline \hline \end{tabular}
\end{table} 
Table 8: Sample instances for demonstrating the experimental set-up for projectile simulation. case was predicted to be approximately 140 m, which may be observed from the simulated trajectories.