Dynamic Mode Decomposition of Unsteady Pressure-Sensitive Paint Measurements for the NASA Unitary Plan Wind Tunnel Tests

Li, Jie; Lash, Lara; Roozeboom, Nettie; Garbeff, Theodore J.; Henze, Christopher E.; Murakami, David D.; Smith, Norman F.; Baerny, Jennifer; Hand, Lawrence; Shaw-Lecerf, Marc; Stremel, Paul M.; Tang, Lucy

doi:10.2514/6.2022-0141

Cited by 6 publications

(1 citation statement)

References 18 publications

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“…Notable examples include the NASA Ames Unitary 11ft. Wind Tunnel experiment on the Space Launch System [7][8][9][10], hypersonic boundary layer separation studies conducted by Running et al on a conical structure resembling HiFire-I at the University of Notre Dame's pulsed arc-heated hypersonic wind tunnel (ACT-1) [11], and the surface pressure measurements of an elliptic cone body at Mach 7.5 in the Calspan University of Buffalo Research Center's hypersonic shock tunnel [12].…”

Section: Introductionmentioning

confidence: 99%

Fast-Responding Pressure-Sensitive Paint Measurements of the IC3X at Mach 7.2

Delgado Elizondo,

Dhanagopal,

Combs

2023

Aerospace

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Global surface pressure measurements of a 5.7% scale AFRL Initial Concept 3.X vehicle (IC3X) were obtained using a fast-responding ruthenium-based pressure-sensitive paint (PSP) at the UTSA Mach 7 Ludwieg Tube Wind Tunnel at two different angles of attack, 0° and 2.5°. Static calibration of the paint was performed over a range of 0.386 kPa to 82.7 kPa to relate luminescent intensity to pressure. Details on the facility, paint preparation, application, calibration, and image processing techniques are provided in the manuscript. The results from statistical, spectral, and proper orthogonal decomposition (POD) analyses are presented to characterize the pressure field observed on the model. The experimental results qualitatively follow the expected trends and correspond to the occurrence of shock waves and expansion fans, which were visualized via Schlieren imaging. The theoretical pressure range obtained from conical shock analysis for 0° agrees with the experimentally derived pressure range for the model, and the outliers are attributed to errors in image registration. This study presents preliminary pressure measurements that pave the way for obtaining time-resolved global PSP measurements to train and validate aerothermodynamic machine learning models.

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