© 2021Background and objectives: Recent developments of low-cost, compact acoustic sensors, advanced signal processing tools and powerful computational resources allow researchers design new scoring systems for acoustic detection of arterial stenoses. In this study, numerical simulations of blood flow inside stenosed arteries are performed to understand the effect of stenosis severity and eccentricity on the turbulence induced wall pressure fluctuations and the generated sound. Methods: Axisymmetric and eccentric elliptic stenoses of five different severities are generated inside a 6.4 mm diameter femoral artery model. Large eddy simulations of pulsatile, non-Newtonian blood flow are performed using the open source software OpenFOAM. Results: Post-stenotic turbulence activity is found to be almost zero for 50 and 60% severities. For severities of 75% and more, turbulent kinetic energy rises significantly with increasing severity. The location of the highest turbulence activity on the vessel wall from the stenosis exit decreases with increasing severity. The maximum level of turbulent kinetic energy seen in 95% severity models is about 9 and 31 times higher than that of 87% and 75% models, respectively. Spectrum of wall pressure fluctuations show that 50 and 60% axisymmetric models are almost silent. The spectrum starts to get richer with 75% severity, and the fluctuation intensity increases with severity. Compared to the axisymmetric models, more activity is observed in the 0–150 Hz band for the 50 and 60% eccentric models. Axial extent of the acoustically active region is also longer in them. Converting wall pressure data into sound revealed that murmurs that can be considered as signs of vascular stenosis are obtained for models with 75% and higher severity. Conclusions: Sound patterns generated from simulation results are similar to the typical sounds obtained by Doppler ultrasonography, and present distinct characters. Together with a sensor technology that can measure these sounds from within the stenosed artery, they can be processed and used for the purpose of non-invasive diagnosis. Computational fluid dynamics studies that simulate large number of cases with different stenosis severities and morphologies will play a critical role in developing the necessary sound databases, which can be used to train new diagnostic devices.