# Detecting Atypical Values and Their Influence on Blast-Induced Seismic Measurement Results
## 2 Materials and Methods
This approach consists of comparing the effects of the output of a given explosive to that of the reference explosive (usually _TNT_) [33]. Most recently, an equivalent _TNT_ weight links the weight of a given explosive to the equivalent weight of _TNT_ using the ratio of their detonation heats [34]:  
\[W_{e}=W_{exp}\frac{H_{exp}^{d}}{H_{TNT}^{d}} \tag{3}\]  
where \(W_{e}\) (kg) is the _TNT_ equivalent weight, \(W_{exp}\) (kg) is the weight of the actual explosive, \(H_{exp}^{d}\) (MJ/kg) is the heat of the detonation of the actual explosive, and \(H_{TNT}^{d}\) (MJ/kg) is the heat of the detonation of the _TNT_. In addition to detonation heat, some authors suggest the use of detonation velocity, detonation pressure, or detonation energy to estimate _TNT_ equivalent mass [33; 35]. The _TNT_ equivalence can be determined experimentally by various types of experiments (e.g., Trauzl test, plate dent, ballistic mortar, and air blasts tests) or can be estimated by thermochemical equilibrium codes [36]. Given that commercial explosives are highly non-ideal, the estimation of _TNT_ equivalence is not a trivial task. It must take into account the effects of the confinement and size of explosive charge on detonation properties. The theoretical estimation of the detonation parameters of commercial explosives applying the Wood-Kirkwood detonation theory coupled with thermochemical code EXPLO5 [37] is the subject of another ongoing research that we are undertaking, which should contribute to a more reliable estimation of the detonation parameters of commercial explosives, and consequently the equivalent weights of commercial explosives needed by Equation (2) in the case of different explosives being used. Since, for this research, only one type of explosive (ELEXIT-2) was utilized, the weight of explosive used in Equation (2) is the actual weight of the explosive charge (cartridge). Equation (1) provides a general form of regression curve [38], which, for the borehole B1 data, is displayed in Figure 2.  
To be able to put measurement data through linear regression, it is required to transform the regression curve (Figure 2) to a straight line, by taking logarithms to the base 10 of both sides of Equation (1):  
\[\log PPV=\log H-\beta\log SD \tag{4}\]  
All measurement values were prepared according to Equation (4) for further analysis. In many different fields, the methods for the detection of atypical values have already been accepted. As there is no clearly defined procedure for the detection of atypical values (outliers) in the measurements of blast-induced seismic effects and their exclusion, each dataset, prepared according to Equation (4), was put through regression statistics in the  
There are certain prerequisites to be able to identify false measurement values. The large number of measurement instruments should be positioned in a single line at predefined distances from the blast. There should be a minimum of 4 instruments in the measurement line for each direction of interest from the blast. After each blast, the measured values should be validated to be eligible for further calculations and analysis. It is reasonable to expect some dispersion of data due to the geology. The number of measurement points for borehole B1 after the exclusion of atypical values, according to each confident interval, is presented in Table 2.  
Measurement data with confidence intervals of 97.73% and 99.99% (Sigma 3 and 4) do not exclude any value; hence, there are no atypical values (outliers) outside of the mentioned intervals.