## 3 Results  
The gray histograms in Figure 4 show the number of acoustic signals during the melting of a water sample with different weights between \(\mathrm{m}=1.0\;\pm\;0.1\) g and \(\mathrm{m}=4.0\;\pm\;0.1\) g. The black lines show the air temperature in the isolated box. All four histograms show a high acoustic activity when the temperature reaches the melting temperature. Two peaks of acoustic activity can be identified. The first peak appears at the beginning of the melting process where the Celsius temperature just reaches a positive value. After an \"activity valley\", another, lower peak appears at the end of the melting phase. Prior to the increase of temperature in Figure 4 at \(t<6\,\mathrm{h}\), the temperature is constant for approximately two hours. This time included, none of the performed measurements show more than five detected events until the temperature reaches \(T\approx-2.5\,^{\circ}\)C. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Phase** & **Time** & **Temperature** \\ \hline constant & \(1\,\mathrm{h}\) & \(T=10\,^{\circ}\)C \\ freezing & \(3\,\mathrm{h}\) & \(\Delta T_{\downarrow}=-8\,^{\circ}\)C h\({}^{-1}\) \\ constant & \(2\,\mathrm{h}\) & \(T=-14\,^{\circ}\)C \\ melting & \(3\,\mathrm{h}\) & \(\Delta T_{\uparrow}=8\,^{\circ}\)C h\({}^{-1}\) \\ constant & \(2\,\mathrm{h}\) & \(T=10\,^{\circ}\)C \\ \hline \end{tabular}
\end{table} 
Table 1: Temperature profile during the measurement in the temperature–controlled box. Figure 4: Time-dependent histogram of acoustic signals, “fluts” per minute, during the melting of ice. Four histograms (**A–D**) for four different amounts of ice (\(\mathrm{m}_{\mathrm{ice}}=(1\,\mathrm{g},\mathrm{2g},\mathrm{3g},\mathrm{4g})\), upper left to lower right) plotted against the time (grey). On the second x-axis (right), the air temperature inside the experimental setup is plotted (black line). The temperature curve confirms the reliable performance of the temperature controlling facility. The experimental setup reaches the target temperature within its limits and stabilizes the temperature at the lower plateau at \(T=-14.00\ \pm\ 0.05\ ^{\circ}\mathrm{C}\). Taking a possible systematic offset from the NTC sensor into account, an air temperature uncertainty of less than \(\Delta T=0.1\,\mathrm{K}\) can be assumed. During the constant raise of target temperature, the temperature shows a small variation of about \(\Delta T\)\(\sim\)30 mK around the target temperature at \(t\)\(\sim\)7 h. The registered time-dependent power that drives the Peltier-cooling element confirms this fluctuation around the constantly rising target temperature (not shown in Figure 4). Both can be explained with the latent heat of the melting process which results an additional \"energy consumption\" in the system. The temperature control unit reacts with a certain delay to this, which results in a slower temperature increase. This is followed by an \"over-steering\" of the temperature control unit and an increase of the temperature above the target temperature. In the upper right corner of each plot, the mass of water and total sum of acoustic events is indicated. As described in Section 2.1, common AE parameters such as AMPL, D, RT and E are calculated for each acoustic event. This allows a later filtering and detailed parameter-based analysis. However, in this experiment, only the RT was used to distinguish between AE signal from the ice-melting and background noise. For this, a RT-filter with a threshold of RT \(\geq\) 0.1 ms was implemented. A different representation of the data can be seen in Figure 5 where all detected AE events are plotted in a scatter plot showing their AMPL and the time of occurrence (gray dots). The histograms in Figure 5 show the accumulated energy per time unit during the melting (black line). The single events, as well as the histograms which are very similar to the histograms in Figure 5 indicate that there is no significant change in the AMPL or acoustic energy of the events along the melting process.