## 6 Conclusions  
This work describes a safety analysis performed for a simplex air data system partially based on synthetic sensors that is certifiable for civil applications. As the present work is funded in the frame of Clean Sky 2, the results are related to the SAT community but they can be easily extended to any civil application and to other aircraft categories, such as UAVs and UAM vehicles. The ADS's main innovation relies on estimation of the flow angles (angle of attack and sideslip) by means of synthetic sensors instead of classical vanes. The synthetic sensors fuse flight data available on board with deterministic algorithms based on pretrained neural networks. In order to perform a safety analysis, MTBF data of the ADS sub-parts are evaluated on a statistical basis. The safety budget is allocated to all ADFs with common FHA and PSSA, whereas the ADF reliability is evaluated using a typical SSA. The safety assessment results of the air data functions are then compared with the safety objectives. The analysis highlights that the simplex ADS solution cannot meet the airworthiness safety objectives due to technological limitations. In fact, the comparison shows that all functions of a simplex ADS have noncompliant reliability with respect to the system specifications. In particular, the air functions (AoA and AoS estimations) based on synthetic sensors cannot meet the safety objectives because they are highly dependent on airspeed measure (ADF1.2). Overall, the most critical ADS sub-parts are identified in anti-icing devices. This limitation is not related to the present application but is related to a technological gap that can be overcome with anti-icing solutions characterizing higher MTBF or by adopting adequate ADS redundancy at the aircraft level in order to enable on-board implementation. Conceptualization, A.L. ; methodology, A.L. ; software, A.L. ; validation, A.L. ; and M.B. ; formal analysis, A.L. ; investigation, A.L. ; resources, A.L. and M.B. ; data curation, A.L. ; writing--original draft preparation, A.L. ; writing--review and editing, A.L. and M.B. ; visualization, A.L. ; supervision, A.L. and M.B. ; project administration, M.B. ; funding acquisition, A.L. and M.B. Both authors have read and agreed to the published version of the manuscript. The project leading to this application has received funding from the Clean Sky 2 Joint Undertaking under the European Union's Horizon 2020 research and innovation programme under grant agreement No. 821140. Not applicable. The authors declare no conflict of interest. The present paper reflects only the author's view, and H2020/Clean Sky 2 is not responsible for any use that may be made of the information it contains. The following abbreviations are used in this manuscript: \begin{table}
\begin{tabular}{c c c c} \hline \hline
**ADF** & \begin{tabular}{c} **SSA Result (from** \\ **Estimated MTBF**) \\ \end{tabular} & \
\begin{tabular}{c} **SSA Result (from** \\ **Manufacturer’s MTBF**) \\ \end{tabular} &
\begin{tabular}{c} **Compliant (with** \\ **Safety Objective**) \\ \end{tabular} \\ \hline ADF1 & \(6.9\times 10^{-5}\) & \(7.7\times 10^{-5}\) & NO \\ ADF2 & \(3.1\times 10^{-5}\) & \(3.1\times 10^{-5}\) & NO \\ ADF3 & \(6.9\times 10^{-5}\) & \(7.7\times 10^{-5}\) & NO \\ ADF4 & \(6.9\times 10^{-5}\) & \(7.7\times 10^{-5}\) & NO \\ \hline \hline \end{tabular}
\end{table} 
Table 7: SSA results of erroneous (or unannuciated) ADF failure conditions estimated starting from the MTBF of ADS sub-parts and compared with the safety objective \(<1\times 10^{-6}\) defined in Section 2.