## 3 Methodology
### Matching Phase:
As a result of an advisory meeting with safety experts, we assumed that the impact of the experts' contribution to the assessment would be proportional to a benchmark 10 year-career experience level. [34; 35]. Based on their career experience, their respective contributions to the assessment were therefore assigned as shown in Table 7. Thus, \(C_{1}+C_{2}+\cdots+C_{m}=1\), where \(C_{1},\ C_{2},\ \cdots,\ C_{m}\) are the contributions of \(\text{expert}_{1},\ \text{expert}_{2},\ \cdots,\ \text{expert}_{m}\), respectively. Step 3. Conduct measurement:  
If the data required for stochastic or statistical assessment is uncertain, inaccurate, or incomplete, then the results of the assessment are unreliable [36; 37]. In fields related to nuclear engineering, researchers have traditionally relied on data from previous studies or the engineering judgment of experts based on past experience. However, it is nearly impossible for an analyst to accurately, precisely, and objectively assess the subject of their analysis as the analyst's judgment is inevitably somewhat subjective and ambiguous [38]. Fuzzy inference-based methodologies have been widely used in various fields to address these disadvantages [39; 40]. In particular, fuzzy inference methods can be very useful in situations where there is a lack of reliable empirical data, which is the case when attempting to assess the risks involved in the decontamination and decommissioning of nuclear facilities; this issue is made even worse due to the unclear correlation between the various radiological, non-radiological, and structural risks. The risk assessment process based on the decontamination and decommissioning risk classification system derived above is performed in the following order: (1) risk assessment modeling, (2) expert interviews, and (3) risk assessment and analysis. The basic risk assessment concept of this study \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Category** & **Item** & **Frequency** & **Percentage (\%)** \\ \hline \multirow{5}{*}{Experience} & \textless{}5 years & 2 & 16.7 \\  & 5–10 years & 5 & 41.6 \\  & 10–15 years & 2 & 16.7 \\  & 15–20 years & 1 & 8.3 \\  & \(\geq\)20 years & 2 & 16.7 \\  & Research Institution & 1 & 8.3 \\  & Experts related to Construction Management & 2 & 16.7 \\ Field & Experts related to Structural Engineering & 2 & 16.7 \\  & General Contractor & 4 & 33.3 \\  & Specialty Contractor & 3 & 25 \\ Sum & & 12 & 100 \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Composition of the experts. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Expert** & **Field** & **Career Experience** & **Impact** & **Contribution (\(C_{i}\))** \\ \hline \(C_{1}\) & Research Institution & 10 & 1 & 0.08 \\ \(C_{2}\) & Experts related to Construction Management & 3 & 0.3 & 0.024 \\ \(C_{3}\) & Experts related to Construction Management & 3 & 0.3 & 0.024 \\ \(C_{4}\) & Experts related to Structural Engineering & 7 & 0.7 & 0.056 \\ \(C_{5}\) & Experts related to Structural Engineering & 20 & 2 & 0.16 \\ \(C_{6}\) & General Contractor & 28 & 2.8 & 0.224 \\ \(C_{7}\) & General Contractor & 8 & 0.8 & 0.064 \\ \(C_{8}\) & General Contractor & 5 & 0.5 & 0.04 \\ \(C_{9}\) & General Contractor & 15 & 1.5 & 0.12 \\ \(C_{10}\) & Specialty Contractor & 8 & 0.8 & 0.064 \\ \(C_{11}\) & Specialty Contractor & 8 & 0.8 & 0.064 \\ \(C_{12}\) & Specialty Contractor & 10 & 1 & 0.08 \\ Sum & & 125 & 12.5 & 1 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Details of experts’ contribution. was based on the MIL-STD 882 standard [41]. In general, the frequency and intensity of risks are considered in the assessment of hazards, which are then divided into several levels [42]. For this study, the intensity and frequency of structural and job risks were each classified into five levels for use in the subsequent risk assessment. The worker risk was calculated by adding the intensity and frequency of job risks and the frequency weights by work of structural risks.