## 4 Construction of the Safety Passage Redundancy Evaluation Model for the Taxiway Bridge
### Fatigue Safe Passage Analysis of the Taxiiway Bridge Based on the Flight Growth Rate
\begin{table}
\begin{tabular}{c c c} \hline \hline
**Flight Growth Rate (\%)** & \
\begin{tabular}{c} **Maximum Deflection at the** \\ **End of the 20 th Year (mm)** \\ \end{tabular} &
\begin{tabular}{c} **Allowable Maximum** \\ **Deflection (mm)** \\ \end{tabular} \\ \hline
3 & 24.98 & 26.03 \\
5 & 25.51 & 26.03 \\
7 & 26.28 & 26.03 \\
9 & 27.46 & 26.03 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: The maximum deflection of the taxiway bridge mid-span considering the annual flight growth rate. Similarly, the annual growth rate of flights continues to increase to 15% [18], the simulation value is extracted, and the relationship is verified. The following curve can be obtained as shown in Figure 12:  
The curve shows that the trend of the relationship value is consistent with the simulation value, and the relative error is very small, which is controlled within 5%, indicating that the relationship is accurate and reliable, and can be used to predict the safe passage redundancy of the taxiway bridge under the fatigue state. Prediction and Analysis of the Remaining Life of the Taxiway Bridge under the Influence of Multiple Indexes  
Through the above analysis, based on the fatigue accumulation state of the taxiway bridge, the aircraft type, load, times, and the annual growth rate of flights can have an impact on the remaining traffic life of the taxiway bridge. By comprehensively considering the maximum deflection value in the middle of the existing span of the taxiway bridge, the number of passing sorties, the average annual growth rate of flights, and the single-wheel load value of the main landing gear of the aircraft, through the correlation analysis of the simulation data obtained in Sections 4.1-4.3, the relationship between the number of operations \(N_{0}\) and the maximum deflection in the middle of the span, the average annual growth rate of flights, and the single-wheel load value of the main landing gear of the aircraft can be calculated as follows:  
\[N_{0}=261732.8+10909.5Y_{t}-1599.5P_{t}+36728.7\alpha \tag{10}\]  
Figure 11: The maximum deflection of the taxiway bridge mid-span under different flight growth rates. Figure 12: Data validation curve. \(N_{0}\) is the sorties that has been operated. \(Y_{t}\) (mm) is the maximum deflection value of the bridge deck mid-span. \(\alpha\) is the value that removes the percentage sign of the annual growth rate of flights. \(P_{t}\) (kN) is the single-wheel load value of the aircraft's main landing gear. After checking, the correlation coefficient \(R^{2}\) = 0.9876, indicating that the correlation between the curve and the data is as high as 98.76%. Several working conditions are proposed to check the accuracy of the formula, as shown below. Working condition A: B747-400 passes through the taxiway bridge along the centerline of the bridge deck at 2857.63 kN. The maximum deflection value at the middle of the existing span is 26.28 mm, with an average annual flight growth rate of 7%. Working condition B: B747-400 passes through the taxiway bridge along the centerline of the bridge deck at 1827.21 kN. The maximum deflection value at the middle of the existing span is 14.41 mm, with an average annual flight growth rate of 0. Working condition C: B747-400 passes through the taxiway bridge along the centerline of the bridge deck at 2857.63 kN. The maximum deflection value at the middle of the existing span is 25.11 mm, with an average annual flight growth rate of 6%. The data in Table 8 show that the relative error of the model is controlled within 5%, which meets the correlation requirements and can be used to deduce the remaining traffic life prediction model of the taxiway bridge under the fatigue state. The analysis in Section 3.3 suggests that the maximum allowable deflection of the taxiway bridge is 26.03 mm.