Research studies on internal, low Reynolds number flows are less commonly found, although they are highly relevant to biomedical applications. Some of these flows with low Reynolds numbers are considered turbulent, including airflow through the glottis in the upper airways and blood flow through an aortic heart valve. In this study, different turbulence methods for an internal bounded flow were evaluated using computational fluid dynamics modeling. Also, laser Doppler anemometry was used to measure the velocity at different locations for validating the computational results. Analysis of the mean velocity and local velocity fluctuations indicated that the large eddy simulation Smagorinsky subgrid-scale turbulence model had the highest agreement with experimental results. The accuracy of the large eddy simulation model in predicting mean flow was followed by RANS Reynolds stress, RANS k-ω, and then DES. However, the RANS models did not resolve turbulent flow fluctuations and eddies that would be the main sources of flow-induced sounds in biomedical applications. In addition, DES did not localize the fluctuating zone properly and underestimated the flow fluctuations in the separation zone for the internal flow at a low Reynolds number. Therefore, LES would be an optimal turbulence model for internal flow with constriction, especially when identifying the sound generation mechanisms.