## 5 Pressure Measurement Experiments for Shockwave Impact  
This study used LabVIEW graphical language with version 2014 SPI [31; 32; 33] to develop automatic monitoring software for shockwave emission. This monitoring software can automatically capture the pressure signals of shockwave impact through the NI USB-6351 data acquisition card [26]. We conducted pressure measurement experiments on the shockwave impact in a water tank to monitor the pressures and distances of the shockwaves emitted from the output tube. We used a tank pressure sensor (\(s_{pt}\)), an output pressure sensor (\(s_{p0}\)), and six soil pressure sensors (\(s_{p1}\),..., \(s_{pm}\), \(m\) = 6), which were buried at six different distances (\(L1\), \(L2\), \(L3\), \(L4\), \(L5\), and \(L6\)) around the shock output tube, and the direction of the shockwaves was selected, as shown in Figure 12. Their distances were from near to far, that is, \(L1<L2<L3<L4<L5<L6\). The calibration procedure is performed for each sensor every year. As a result, \(s_{pt}\) was calibrated with an accuracy of \(\pm 1\) kPa, \(s_{p0}\) was calibrated with an accuracy of \(\pm 0.1\) MPa, and \(s_{p1}-s_{p6}\) were calibrated with an accuracy of \(\pm 0.01\) MPa. Figure 11: A visual observation experiment of a side-view shockwave emission: **(a)** the shockwaves is just emitted; **(b)** shockwaves are in the process of being emitted; **(c)** the ejected shockwaves create large waves. Figure 10: A visual observation experiment of a top-view shockwave emission: **(a)** the shockwaves are just emitted; **(b)** shockwaves are in the process of being emitted; **(c)** the ejected shockwaves create large waves. In addition, considering that the speed of the shockwave is too fast, we used the buffer sampling method to directly capture all the pressure data detected by the six sensors in 1 s and store them in the buffer of the USB-6351 data acquisition card. This buffer can store 800,000 data allocated to eight channels and 100,000 records per channel. The monitoring host then reads the pressure data from the buffer and puts them into the computer for processing, drawing, and analysis. In the automatic monitoring software, the user can first set various monitoring parameters in the parameter-setting screen shown in Figure 13, such as tank pressure \(P_{t}\) (600 kPa), soil texture (Silt), pressure measurement points \(N\) (8), tank volume \(V_{t}\) (5000 cm\({}^{3}\)), sampling rate \(R_{s}\) (100,000 Pt/Sec), the number of samples \(N_{s}\) (100,000 Pt), the file name (C\(\backslash\)Soil Loosening Data\(\backslash\)Test Results.xls), and shock output tube parameters such as \(d\) (40 cm), \(d1\) (10 cm), \(d2\) (20 cm), \(L1\) (10 cm), \(L2\) (20 cm), \(L3\) (25 cm), \(L4\) (30 cm), \(L5\) (35 cm), and \(L6\) (40 cm). The values in brackets are user-set values. Figure 12: Shockwave impact monitoring diagram. Figure 13: Shockwave impact parameter-setting screen. Figure 14 shows the pressure-monitoring screen of shockwave impact. The top of the screen displays the various parameters set by the user. The middle of the screen contains eight pressure curve graphs (\(N\) = 8), including the tank graph (\(p_{t}\) curve), output graph (\(p_{0}\) curve), and \(L1\) graph (\(p_{s1}\) curve)\(-L6\) graph (\(p_{s6}\) curve). They display the pressure data measured by eight sensors (\(s_{pt}\), \(s_{po}\), \(s_{p1}-s_{pg}\)). The system automatically displays the maximum pressure of each curve in the center of the curve graph to help users observe and analyze the effectiveness of shockwave impact. We define the maximum pressure \(p_{s1 max}\) of \(p_{s1}\) curve data as in Equation (18). The displayed minimum (\(x_{min}\)) and maximum (\(x_{max}\)) values on _the_\(X\)-axis are defined in Equations (19) and (20):  
\[p_{s1 max}=\max(p_{s1i},i=1,\ \ldots,N_{s}) \tag{18}\]  
\[x_{min}=\left[x_{k}-\frac{N_{x}}{2}\right]\text{, }\text{where }p_{s1k}=p_{s1 max} \tag{19}\]  
\[x_{max}=x_{min}+N_{x} \tag{20}\]  
where \(N_{x}\) is the number of display points on the \(X\)-axis.