Data-driven Pressure Recovery in Diffusers

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.

Authors

Publication Details

Journal
Maryland Shared Open Access Repository (USMAI Consortium)
Published
2025-12-11
DOI
https://doi.org/10.13016/m2iowt-fxzj
Primary Topic
Model Reduction and Neural Networks
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Data-driven Pressure Recovery in Diffusers

Michael Amitay, Özgür Tümüklü, Juan A. Paredes, Rowen Costich et al.
Maryland Shared Open Access Repository (USMAI Consortium)
Model Reduction and Neural Networks
article

Data-driven Pressure Recovery in Diffusers

Michael Amitay, Özgür Tümüklü, Juan A. Paredes, Rowen Costich, Ankit Goel, Meliksah Koca
article en

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.

Maryland Shared Open Access Repository (USMAI Consortium)
Affordable and clean energy
Openalex Percentile: Top 27%
Model Reduction and Neural Networks
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

Data-driven Pressure Recovery in Diffusers — Michael Amitay, Özgür Tümüklü, et al. · Maryland Shared Open Access Repository (USMAI Consortium) (2025) | TGRS Research Map | TGRS