# Reliability Assessment of Space Station Based on Multi-Layer and Multi-Type Risks
## 8 Conclusions and Future Works  
This paper takes the space station as the research objective, and proposes a PRPA method to assess the configuration reliability in the early stage. First, the multi-layers and multi-type risks are identified. Through the qualitative risk feature analysis, the key risks are determined, and the high load risks are determined by the quantitative risk feature analysis. Through the ET and FT methods, the assessment model is built, and the high load risks' occurrence probability and propagation probability data are collected from the database. Based on the above work, the configuration reliability is assessed and the weakness of the configuration mission is determined at the same time. Along with the space station configuration process, the PRPA method still needs to be improved in the  
\begin{table}
\begin{tabular}{c c c c c} \hline
**No.** & **Risk Symbol** & \(\mathbf{P_{oi}}\) & \(\mathbf{P_{pi}}\) & \(\mathbf{P_{ai}}\) \\ \hline
1 & RP11 & \(6.4051\times 10^{-3}\) & \(3.8054\times 10^{-3}\) & \(4.937\times 10^{-3}\) \\
2 & RP12 & \(1.4046\times 10^{-3}\) & \(2.1985\times 10^{-4}\) & \(5.557\times 10^{-4}\) \\
3 & RP13 & \(1.2188\times 10^{-3}\) & \(4.6507\times 10^{-4}\) & \(7.529\times 10^{-4}\) \\
4 & RP14 & \(4.156\times 10^{-3}\) & \(9.421\times 10^{-5}\) & \(6.258\times 10^{-4}\) \\
5 & RP15 & \(5.5806\times 10^{-3}\) & \(8.871\times 10^{-5}\) & \(7.036\times 10^{-4}\) \\
6 & RP21 & \(5.9727\times 10^{-4}\) & \(7.2391\times 10^{-5}\) & \(6.575\times 10^{-4}\) \\
7 & RP22 & \(6.7152\times 10^{-5}\) & \(5.4309\times 10^{-5}\) & \(6.039\times 10^{-5}\) \\
8 & RP23 & \(7.82\times 10^{-5}\) & \(3.9489\times 10^{-5}\) & \(5.557\times 10^{-5}\) \\
9 & RP24 & \(6.4778\times 10^{-5}\) & \(3.7065\times 10^{-5}\) & \(4.9\times 10^{-5}\) \\
10 & RP31 & \(4.1927\times 10^{-5}\) & \(3.5042\times 10^{-5}\) & \(3.833\times 10^{-5}\) \\
11 & RP32 & \(5.4695\times 10^{-5}\) & \(1.5461\times 10^{-5}\) & \(2.908\times 10^{-5}\) \\
12 & RP33 & \(2.1032\times 10^{-5}\) & \(1.234\times 10^{-5}\) & \(1.611\times 10^{-5}\) \\
13 & RP34 & \(3.9967\times 10^{-4}\) & \(7.296\times 10^{-6}\) & \(5.4\times 10^{-5}\) \\
14 & RP35 & \(1.3215\times 10^{-5}\) & \(6.6503\times 10^{-6}\) & \(9.343\times 10^{-6}\) \\
15 & RP36 & \(3.3989\times 10^{-2}\) & \(2.1879\times 10^{-6}\) & \(2.727\times 10^{-4}\) \\ \hline \end{tabular}
\end{table}
Table 6: High load risks probabilities of the space station configuration mission.  
\begin{table}
\begin{tabular}{c c} \hline
**End State** & **Mean Probability** \\ \hline MS & 0.9912 \\ LOC & 0.002733 \\ LOP & 0.0007357 \\ LOM & 0.005322 \\ \hline \end{tabular}
\end{table}
Table 7: Configuration mission reliability final states probabilities.  
following ways to satisfy the whole configuration assessment request: (1) building more exact risk propagation models to determine propagation paths; (2) building more accurate assessment probability calculation methods to improve assessment accuracy; (3) carrying out deeper reliability assessment result analysis.  
Conceptualization, X.L.; data curation, X.L. and F.L.; methodology, X.L.; formal analysis, X.L.; formal analysis, X.L.; writing--original draft preparation, X.L. All authors have read and agreed to the published version of the manuscript.  
This research was funded by the National Natural Science Foundation of China grant number 51875089.  
Not applicable.  
The data presented in this article are generated during the study.  
The authors declare no conflict of interest.