# Acoustic Emission-Based Method for IFSS Characterization in Single-Fiber Fragmentation Tests
## 4 Conclusions  
This article presents a method for calculating the interfacial shear strength in single-fiber fragmentation tests using acoustic emission techniques combined with statistical distribution fitting. Based on the results, the conclusions are drawn as follows:  
1. Specimens manufactured without fiber do not exhibit AE activity in their signals. Therefore, the presence of bursts in the AE signals measured during the SFFTs is related to the fiber failure mechanisms inside the specimens. 2. The fragment lengths observed in the specimens after the SFFTs follow a distribution with a positive skew. Therefore, the distributions that best fit the data are the lognormal and gamma distributions. 3. A methodology is developed to estimate the average fragment length using a fitted gamma distribution based on the number of fragments measured with the AE method. The values obtained from this distribution allow the incorporation of the positive skew observed in the fragment lengths into the calculation of IFSS using AE. 4. The IFSS error from the AE-arithmetic method, compared to the optical microscope method, is 30.37% at a 95% confidence level. On the other hand, the error from the AE-fitted method is 14.16% at a 95% confidence level. The AE-fitted method provides significantly better results than the AE-arithmetic method, as it considers the distribution of fragment lengths experimentally observed in the SFFTs. 5. A potential source of error lies in the mounting of the AE sensor, where a mounting support is used to press the sensor against the specimen to facilitate AE detection and prevent slippage between the two elements. However, as the specimen deforms and its cross-sectional area reduces, the pressure of the support also decreases, which could cause movements detected by the sensor and introduce an error in the IFSS calculation. The main advantages of the AE-fitted method compared to the optical method are the elimination of the labor hours required for fragment counting and measurement under the \begin{table}
\begin{tabular}{c c c c} \hline \hline  & \multicolumn{3}{c}{**IFSS Error [\%]**} \\ \cline{2-4}  & \multicolumn{2}{c}{**AE-Fitted Method**} & \multicolumn{2}{c}{\
\begin{tabular}{c} **AE-Arithmetic** \\ **Method** \\ \end{tabular} } \\ \hline \multicolumn{2}{c}{**Mean Individual Error**} & 10.42 & 22.36 \\ \hline \multirow{3}{*}{
\begin{tabular}{c} 50\% \\ **Confidence** \\ **interval** \\ \end{tabular} } & 50\% & 10.52 & 22.57 \\  & 75\% & 11.80 & 25.32 \\  & 95\% & 14.16 & 30.37 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Confidence intervals for the IFSS error of the AE method compared to the optical microscopy method. The two methodologies used to calculate the average fragment lengths in the AE method are analyzed: arithmetic mean and fitted distribution. optical microscope, as well as its ease of application in composite materials with opaque matrices and interfaces with high adhesion. To advance the understanding and characterization of interfacial properties in micromechanical testing of composite materials through acoustic emissions, the following research lines are proposed:  
1. Use of multiple AE sensors: Implementing two or more AE sensors on the specimen allows locating events within the specimen through triangulation and thus estimating the length of the generated fragments. This approach could be evaluated in combination with different specimen geometries, considering the influence of sensor position on the quality of the detected signals. 2. Influence of IFSS on the measured AE signal: The objective is to analyze how different adhesion levels affect the generation and burst detection. It could be evaluated whether a higher IFSS alters the AE indicators of the detected bursts, as stronger interfaces could generate different signals due to higher energy accumulation before rupture. Conceptualization, F.R., F.M., A.S. and C.V.; methodology, F.R., F.M., A.S. and C.V.; Software, F.R. and F.M.