1-D FLEET velocimetry in an overexpanded supersonic air jet

The study of non-adapted supersonic jets is essential for optimizing nozzle designs, reducing jet noise and improving the performances and durability of aerospace propulsion systems. Experimental data retrieved using non-intrusive optical diagnostics in representative test benches are necessary to optimize and validate the numerical models describing the complex physics of these jets and their associated shock structures. Femtosecond Laser Electronic Excitation Tagging (FLEET) is a molecular tagging velocimetry technique of increasing interest due to its straightforward implementation and its ability to operate without particle or gas seeding. This technique constitutes a relevant complement to traditional particle-based velocimetry for the investigation of high-speed flows, and for probing the steep velocity gradients occurring in the vicinity of shock structures in non-adapted supersonic jets. We report here a measurement campaign of FLEET velocimetry in a large-scale test facility called ADIJE at ONERA to characterize a round overexpanded supersonic jet of air. One-dimensional velocity measurements were performed at 15 axial positions along the jet centerline to map the mean axial velocity from the nozzle exit to two nozzle lip diameters downstream. To our knowledge, it was the first time that FLEET was applied to map out the velocity in an overexpanded jet with such a regular and extended spatial coverage. In particular, the explored area encompasses a strong normal shock also called "Mach disk" characterized by a sharp velocity gradient. The measured axial velocity drops from 1000 ± 50 m/s to 220 ± 30 m/s over one millimeter. The velocity mapping also provides insight into the jet topology in the vicinity of the shock. Additionally, a comparison was made with Particle Image Velocimetry (PIV) measurements and numerical results from Large Eddy Simulation (LES). The results obtained here with FLEET, which is a particle-free technique, constitute a valuable dataset for supersonic jets characterization and for improving and validating numerical models.