Demonstration and verification of exact DMD analysis applied to double-pulsed schlieren image of supersonic impinging jet

Ohmizu, Kasumi; Ozawa, Yuta; Nagata, Takayuki; Nonomura, Taku; Asai, Keisuke

doi:10.1007/s12650-022-00836-9

Cited by 10 publications

(1 citation statement)

References 44 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The recent technology advancement allows experimentally measuring the time-resolved data using a high-speed camera, and the data-driven analysis such as the proper orthogonal decomposition (POD) (Berkooz et al, 1993) or dynamic mode decomposition (Schmid, 2010) is often employed. There are many attempts to identify the screech tone from the time-resolved schlieren images (Li et al, 2021;Lim et al, 2020;Rao et al, 2020;Ozawa et al, 2018;Mercier et al, 2017;Ohmizu et al, 2022). However, a conventional high-speed camera still does not have a sufficient sampling rate for the visualization of the entire flow field with high spatial resolution.…”

mentioning

confidence: 99%

Spatiotemporal Superresolution Measurement based on POD and Sparse Regression applied to a Supersonic Jet measured by PIV and Near-field Microphone

Ozawa,

Nagata,

Nonomura

2022

Preprint

Self Cite

View full text Add to dashboard Cite

The present study proposed the framework of the spatiotemporal superresolution measurement based on the and sparse regression with dimensionality reduction using the proper orthogonal decomposition (POD). The non-time-resolved particle image velocimetry (PIV) and the time-resolved near-field acoustic measurements using microphones were simultaneously performed for a Mach 1.35 supersonic jet. POD is applied to PIV and microphone data matrices and the sparse linear regression model of the reduced-order data is calculated using the least absolute shrinkage and selection operator regression. The effects of the hyperparameters of the superresolution measurement were quantitatively evaluated through randomized cross-validation. The superresolved velocity field indicated the smooth convection of the velocity fluctuations associated with the screech tone, while the convection of the large-scale structures at the downstream side was not observed. The proposed framework can reconstruct the unsteady fluctuation with multiple frequency phenomena, although the reconstruction is limited to the phenomena that is associated with the microphone output.

show abstract