Data-driven Pressure Recovery in Diffusers
Abstract
This paper investigates the application of a data-driven technique based on retrospective cost optimization to optimize the frequency of mass injection into an S-shaped diffuser, with the objective of maximizing the pressure recovery. Experimental data indicated that there is an optimal injection frequency between 100 Hz and 300 Hz with a mass flow rate of 1 percent of the free stream. High-fidelity numerical simulations using compressible unsteady Reynolds-Averaged Navier-Stokes (URANS) are conducted to investigate the mean and temporal features resulting from mass injection into an S-shaped diffuser with differing injection speeds and pulse frequencies. The results are compared with experiments to confirm the accuracy of the numerical solution. Overall, 2-D simulations are relatively in good agreement with the experiment, with 3-D simulations currently under investigation to benchmark the effect of spanwise instabilities. Simulation results with the proposed data-driven technique show improvements upon a baseline case by increasing pressure recovery and reducing the region of flow recirculation within the diffuser.
Cite
@article{arxiv.2512.10801,
title = {Data-driven Pressure Recovery in Diffusers},
author = {Juan Augusto Paredes Salazar and Ankit Goel and Rowen Costich and Meliksah Koca and Ozgur Tumuklu and Michael Amitay},
journal= {arXiv preprint arXiv:2512.10801},
year = {2025}
}
Comments
To be presented at the 2026 Scitech Forum