## 3 Materials and Methods  
### Workflow  
The goal of the work in this paper is to meet the needs of field experts and address the problem of damage feature visualization and the analysis of multimodal data in the NDE of composite materials, rather than simply completing the visualization of AE and DIC data. To determine the analysis requirements for multimodal data, we have closely collaborated with an expert in the field of materials science (referred to as [PERSON]) and their team (referred to as [PERSON]) over an extended period. [PERSON], who has 15 years of research experience in material damage and extensive expertise in NDE, has provided the necessary domain knowledge for the design of NDEExplorer. To ensure the objectivity of expert verification, we strictly adhere to standardized, systematic procedures throughout the analysis process. [PERSON] (the lead expert) and [PERSON] (in an advisory capacity) have contributed to the identification and verification of the requirements through multiple discussions and feedback sessions. Specifically, [PERSON] is responsible for determining the main theoretical framework and data requirements, while team member [PERSON] has assisted with and supplemented the data collection, selection of analysis methods, and technical details. The feedback from all experts was facilitated through regular meetings and written reports, and their perspectives were compared to maintain consistency and accuracy in the verification process. We further clarify the expert verification process in the case analysis section to ensure the transparency and traceability of our research at every stage. Together, we identified the key needs for analyzing and integrating AE and DIC data, which are summarized as a list of requirements (as shown in Table 1). These requirements cover the critical issues in NDE analysis, and Figure 2 shows the entire workflow. \begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline \hline
**Requirement Category** & **Visualization Task** & **Analytical Goals** \\ \hline Damage analysis & T1: Design a materials damage visualization workflow. & G1, G2 \\ Feature processing & T2: Select an appropriate clustering method. & G3 \\  & T3: Optimize image processing methods. & G2 \\ Information fusion & T4: Combine AE and DIC data based on damage severity. & G4, G5 \\ System optimization & T5: Visualization of damage retrogression. & G5 \\  & T6: Incorporate evaluation metrics for clustering methods. & G3, G5 \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Visualization tasks with requirement category and the corresponding analytical goals. Data pre-processing. The AE and DIC data acquisition of material damage needs to be consistent, laying the foundation for the fusion analysis of multimodal data. During data pre-processing, multimodal data are processed into formats that meet the analysis requirements according to the requirements of T1-T5. Preliminary stage. Our visual analytics tool design process began with qualitative interviews with experts in the field, aimed at understanding existing issues. E0 reported that their research mainly focuses on identifying material failure modes using various NDE methods, but earlier research lacked consistency in the visualization process. Although many related works showcase simplistic visualization charts, there is still no standard NDE procedure, resulting in significant time and financial costs in damage analysis [35; 36]. Therefore, E0 holds that an ideal visualization system can (G1) explore material damage processes to solve this issue, (G2) improve user experience, and (G3) increase the accuracy of damage pattern recognition. Iterative stages. We iteratively communicated with E0 and their team members based on the requirements for the designed visualization system. After multiple rounds of refinement and adjustments, the experts suggested that by integrating AE and DIC data, (G4) the results of a single NDE method could be cross-verified.