## 5 Conclusions  
This research undertook a comprehensive investigation into predicting interior noise in a tiltrotor aircraft using two methods: advanced transfer path analysis (ATPA) and statistical energy analysis (SEA). The results presented in this study confirm the reliability of the well-known ATPA method as a valuable tool for characterizing the interior noise in an aircraft, as the noise levels calculated using ATPA match with those obtained via experimental measurements at two target points within the cabin. Moreover, this study involved a comparison between the ATPA structure-born noise levels and the results from an aircraft SEA model. For this comparison, this research introduced a hybrid experimental-SEA model to predict structural-borne noise. The model utilizes input data derived from the ATPA campaign test and a finite element model of the aircraft. In this model, ACTRAN is used for the SEA calculations. Overall, both ATPA and the hybrid experimental-SEA model exhibited a consistent trend in structural-born noise prediction. However, a noteworthy average difference of 9.4 dB was observed between the two methods in the one-third octave band noise range of 63 Hz to 1250 Hz. Importantly, this disparity could be significantly reduced via the adjustment of the acoustic damping loss factor (DLF) in the SEA model. This adjustment led to an improved alignment between the overall noise pressure predictions of the ATPA and SEA methods, with differences of 4.1 dB and 5.4 dB observed at Target 1 and Target 2, respectively. Additionally, this study highlighted the efficiency of the hybrid SEA model, particularly at higher frequencies, in analyzing complex structures such as aircraft. Compared with the finite element method (FEM), this approach demanded fewer mode shapes for noise predictions at high frequencies. In the current study, the interior noise was predicted to be up to 4 kHz, utilizing mode shapes of up to 1250 Hz. This is of significant practical importance, as acquiring mode shapes using FEM models can be both time-consuming and resource-intensive at high frequencies. Conceptualization, S.S., A.S.T., P.V.R.S. and E.C.M. ; methodology, S.S., A.S.T., P.V.R.S. and E.C.M. ; software, S.S., A.S.T. and G.B. ; validation, S.S., A.S.T., P.V.R.S. and E.C.M. ; formal analysis, S.S., A.S.T. and E.C.M. ; investigation, S.S., A.S.T. and E.C.M. ; resources, P.V.R.S. and A.P. ; data curation, E.C.M. and A.P. ; writing--original draft preparation, S.S. and A.S.T. ; writing--review and editing, S.S., A.S.T. and E.C.M. ; visualization, S.S., A.S.T. and E.C.M. ; supervision, P.V.R.S., E.C.M. and A.P. ; project administration, P.V.R.S., E.C.M. and A.P. ; funding acquisition, P.V.R.S., E.C.M. and A.P. All authors have read and agreed to the published version of the manuscript. This research was carried out in the framework of the PIANO project (Path Identification for Active Noise Control), funded by EU Horizon 2020 and Clean Sky JU under grant agreement no. 885976. The APC was funded by EU Horizon 2020 and Clean Sky JU. Not applicable. The data are not publicly available due to confidentiality restrictions. **Acknowledgments:** The present work was carried out in the framework of the PIANO project (Path Identification for Active Noise Control), funded by EU Horizon 2020 and Clean Sky JU under grant agreement no. 885976. **Conflicts of Interest:** Authors [PERSON] and [PERSON] were employed by the Leonardo Company. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.