## 3 Validation of the Computational Model  
To demonstrate the validity of the computational model and find the most appropriate combination of boundary conditions, the five simulation cases shown in Table 1 were compared. Figure 5 represents the pressure evolution at the pressure sensors in the supraglottal channel of the synthetic larynx model (P1-P5 in Figure 1) for one oscillation cycle and pressure evolutions obtained from the simulations. The three experimental pressure values at an axial position were averaged and compared with the pressure values acquired at the corresponding axial position at the center axis of the numerical model. The experimental data were best reproduced by the simulation cases C3 and C4, which have the shorter supraglottal channel, and the time-varying pressure \(\mathrm{P}_{60}^{{}^{\prime}}(\mathrm{t})\) taken from the experimental model at x = 60 mm (Figure 3b) as the outlet pressure boundary condition. In contrast to the cases C1 and C2, the choice of the time-varying outlet pressure in C3 and C4 is the key feature to produce a supraglottal flow field that is consistent with the experiments. The configuration C5 with longer supraglottal channel did indeed improve the consistency of the pressure distribution over 2/3 of the cycle, but showed deviations in the last third of the cycle, as shown in Figure 5. Furthermore, the corresponding L\({}^{2}\) relative error norm between the experimental and simulated pressure evolutions (\(\mathrm{Err}_{\mathrm{rel}}^{1,2}=\sqrt{\sum_{t=0}^{T}(P^{\prime}(t)-P(t))^{2 }/\sum_{t=0}^{T}P^{\prime}(t)^{2}}\)[66]) at each position provided in Table 3 revealed that C4 with the applied mean value of the experimental subglottal pressure (\(\overline{P^{\prime}_{\mathrm{s}}}=3251\) Pa) at the inlet has the smallest deviation of the pressure evolution at all five axial positions. Especially in the region immediately downstream of the vocal folds, the L2 error of C4 is significantly smaller than for C3. Therefore, the most appropriate simulation case regarding the boundary conditions and length of the supraglottal channel is C4. Figure 6 shows the velocity fields in the supraglottal channel in the mid-coronal plane of C4 compared with the averaged flow field obtained from the PIV measurements. Configuration C4 reproduced the typical glottal jet deflection caused by the interaction between the jet and a large recirculation area in the supraglottal channel [50; 53; 59; 67]. Moreover, the simulated flow field shows small-scale fluctuations as shear layer instabilities that do not exist in the PIV-based flow field owing to the phase averaging. The length of the jet is also comparable between the numerical and experimental models, with slightly higher velocity values in the numerical model. This is also visible in the velocity evolution graphs in Figure 7, representing the magnitude of the velocity along the center axis of the supraglottal channel for an oscillation cycle of the computational and experimental models. The trends of the velocity evolutions are similar, especially at 5 and 10 mm downstream of the glottis exit. At larger distances, higher strength turbulent flow structures occurred in the instantaneous flow field of the numerical model. As mentioned above, those turbulent flow fluctuations are not evident in the phase-averaged flow field in the PIV measurements. The higher velocity of the jet may be due on the one hand to the phase averaging of the experimental velocities and on the other to the different subglottal pressure values between the experiment for the PIV measurement and that for supraglottal pressure measurement. The latter is the basis of the numerical model in this study. Furthermore, it seems that the jet started to develop sooner and shut off later in the cycle in the numerical case, which may be due to the different glottal area waveforms in the two experiments and also the small leakage at the beginning and end of the cycle in the numerical model.